A review on hybrid electric vehicles architecture and energy management strategies

A review on hybrid electric vehicles architecture and energy management strategies

Renewable and Sustainable Energy Reviews 53 (2016) 1433–1442 Contents lists available at ScienceDirect Renewable and Sustainable Energy Reviews jour...

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Renewable and Sustainable Energy Reviews 53 (2016) 1433–1442

Contents lists available at ScienceDirect

Renewable and Sustainable Energy Reviews journal homepage: www.elsevier.com/locate/rser

A review on hybrid electric vehicles architecture and energy management strategies M.F. M. Sabri, K.A. Danapalasingam n, M.F. Rahmat Faculty of Electrical Engineering, Universiti Teknologi Malaysia, UTM Skudai, 81310 Johor, Malaysia

art ic l e i nf o

a b s t r a c t

Article history: Received 1 February 2015 Received in revised form 6 June 2015 Accepted 18 September 2015 Available online 10 November 2015

Faced with environmental issues caused by fossil fuel burning in the industrial and transportation sectors, innovations towards cleaner solutions to replace the ever diminishing fossil fuels have been the focus of not only researchers but governments all around the world. The hybrid electric vehicle (HEV) technology is the result of the desire to have vehicles with a better fuel economy and lower tailpipe emissions to meet the requirements of environmental policies as well as to absorb the impact of rising fuel prices. The objectives are met by combining a conventional internal combustion engine (ICE) with one or more electric motors powered by a battery pack that can be charged using an on-board generator and the regenerative braking technology to power the transmission. The challenge is to develop an efficient energy management strategy (EMS) to satisfy the objectives while not having a reduced vehicle performance. In this paper, EMSs that are proposed and developed in the recent years are revisited and reviewed. Additionally, the Plug-in HEV is discussed in a new perspective from the EMS point of view. The through-the-road (TtR) HEV with in-wheel motors (IWM) is a fairly new concept in the HEV design that features less complicated configuration with reduced hardware requirements and lower cost. Recent research findings are evaluated throughout this paper leading to a hypothetical TtR HEV materialization. A thorough discussion is made encompassing the advantages and disadvantages of the concept, its performance compared to conventional HEVs and the way forward. & 2015 Elsevier Ltd. All rights reserved.

Keywords: Hybrid electric vehicle (HEV) Energy management strategy Plug-in HEV Through-the-road HEV

Contents 1. 2.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HEV advantages and review of recent energy management strategies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Online energy management strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Off-line energy management strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Plug-in HEV (PHEV) influence. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Paving ways for TtR HEV concept . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1. Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2. Energy management strategy and performance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgement. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1. Introduction A global reality that the world is facing at the moment is the deterioration in environmental conditions. It is mostly due to n

Corresponding author. E-mail address: [email protected] (K.A. Danapalasingam).

http://dx.doi.org/10.1016/j.rser.2015.09.036 1364-0321/& 2015 Elsevier Ltd. All rights reserved.

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continuous and uncontrolled emissions of hazardous and polluting elements to the atmosphere from various segments of human activities. Burning of fossil fuels in industrial and transportation sectors is widely acknowledged as the major contributing factor. Fossil fuels have been the backbone of world civilizations that have seen rapid progress since the introduction of machines into the industrial sector and vehicles using internal combustion engines

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(ICEs). However, it is a finite element which has resulted in the price going onto a steady hike as the result of increasing demand. However, the end of heavy reliance on fossil fuel is in the foreseeable horizon as its reserve are being depleted at a rate at which there is no option for researches than to come up with immediate alternative energy solutions. Most if not all mega size oil field around the world have been discovered during or prior the 1960s and as production and demands are only trending upwards, various studies has projected that the global petroleum production will reach its peak around the year 2030 before facing a steady decline [1–5]. The biggest challenge is to come up with better or equivalent solutions that are not just economically viable but also environmentally friendly. The industrial sector is experiencing a surge in the adoption of renewable or green energy in electricity generation [6]. More and more countries all over the world are increasing or imposing a certain target to be achieved in the near future for their share of clean energy sources which include solar, wind, geothermal, etc. [7]. The transportation sector has also been contributing innovations towards greener vehicles with the ultimate objective of eliminating hazardous tailpipe emissions. In recent years, hybrid electric vehicles (HEVs) have thrived as a lucrative solution to the aforementioned problems with its intermediate approach to achieve superior mileage and low tailpipe emission compared to conventional ICE vehicles. HEV is a term used to describe vehicles that use ICEs in combination with one or more electric motors (EMs) connected to a battery pack as a secondary energy storage system (ESS) providing propulsion to the wheels either together or separately [8]. It is a culmination of mechanical, electrical, electronic and power engineering technologies embracing the best of both conventional ICE vehicles and electric vehicles (EVs). The most notable advantages that an HEV possesses over a pure EV are superior mileage and flexibility in the sizing of the components [9]. The former is due to the presence of an on-board generator to charge the ESS plus the ability to recover energy via regenerative braking allowing for the sustenance of the state-of-charge (SoC) of the ESS. The latter allows for the use of a smaller, more efficient ICE to achieve optimum fuel economy. The ICE in HEV operates within its most efficient region most of the time and can be switched ON/OFF when necessary depending on the energy management strategy (EMS) [8]. In general, HEVs can be classified into three categories based on their design characteristics namely series, parallel and power-split series-parallel, all have their own list of benefits which will be discussed further in the following sections. This paper aims to pave ways for a more recent concept that retains its own set of merits that is the through-the-road (TtR) HEV. A TtR HEV has an ICE and one or more EMs that provide traction forces of front and rear wheels respectively [9]. By the concept, the TtR HEV is classified as a parallel HEV. However, in a TtR HEV, the two sources of traction force are summed up “through the road” whereas in a conventional HEV, torques from different sources are combined in the transmission [9]. The proposed design considered here is a TtR HEV equipped with an ICE that drives the front wheels, and two in-wheel motors (IWMs) to provide traction forces to the rear wheels as shown in Fig. 1. The main issue in the development of HEVs is the management of the power flow between fuel and ESS that contributes to vehicle motion. The difficulty arises given the limited energy supply from the ESS and the requirements to minimize fuel consumption and exhaust emissions. It is a challenging task to satisfy the constraints and the requirements simultaneously, and often trade-offs have to be made to obtain an optimal solution. The problem is further exacerbated by the desire of not to have a reduced vehicle performance. Regardless of the type of HEV, the performance of the vehicle in terms of fuel economy and tailpipe emission depends

ICE

IWM1

IWM2

Fig. 1. Top view of a TtR HEV with rear IWMs.

heavily on the chosen EMS which has been the topic of interest for many researchers [10]. This paper will review some of the most recent approaches to the EMS problem in the recent years while going into considerable details of the proposed methods [11–19]. The plug-in HEV (PHEV) has recently captured considerable amount of interests from researchers given its enhanced approach to the issues of fuel economy and tailpipe emission [20–32]. PHEV is a type of HEV which can be plugged-in and charged using a socket outlet from the grid. This gives a PHEV the ability to run exclusively on electricity before the ICE kicks in when the battery SoC reaches a pre-set lower threshold value [33,34]. PHEVs differ from conventional HEVs in a way that the ESS is considered as the primary energy source. This has given a new dimension to the EMS approach for a better fuel economy as PHEVs can operate in both charge depletion (CD) and charge sustaining (CS) modes [20,34]. The influence of PHEVs and its regards will be discussed in further details in Section 3. There are several papers from since the last decade and even recently which previously have contributed to the compilation of reviews of EMS from various authors [10,33,35–44]. However, with the advancement and introductions of newer techniques in automotive technology, the author sees EMS for HEV as an ever evolving topic that will continue to attract new ideas for many years to come. The main objective of this review paper is not only to contribute to the growing list of discussions regarding recent proposals for EMS but also as an attempt to direct more attention to the realization of TtR HEV with rear IWMs which is the main research interest of the author. As the matter of fact, there are currently very few references that can be found regarding the configuration in question and this paper will hopefully fill that gap. This paper is organized as follows. After the brief introduction in Section 1, Section 2 will showcase the advantages of HEV in general and the review on EMS from recent years. Section 3 elaborates the PHEV, its influences to the EMS problem and how it might be applicable in the TtR concept. Section 4 discusses ways on how the TtR HEV concept can be hypothetically materialized by considering various points raised in the previous sections. Section 5 concludes the paper.

2. HEV advantages and review of recent energy management strategies In the beginning, the most sought after and immediate solutions spearheading the effort to achieve emission-free vehicles are EVs and fuel cell vehicles (FCVs). Although both solutions are theoretically sustainable and emission free, they bear a number of issues which hinder their immediate mass production and wider public acceptance. FCVs are currently still in the early stages of its development cycle and the technology is yet to reach a mature state as researchers and manufacturers are still working out on

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cost reduction and performance optimization [33,45]. On one hand, the near future target market for the technology is public transportations. On the other hand, it is still a magnitude away from actually making it into private vehicles sector mainly due to safety measures [33]. EVs use rechargeable battery packs, commonly lithium-ion (Liion) batteries as its source of energy to power one or more EMs for propulsion. It operates in CD mode and ideally, the battery pack needs to be fully recharged before every trip to ensure maximum operating range. It is greatly being held back by the current battery technology which is still unable to provide high energy density batteries in a smaller, lighter and inexpensive package [46]. The result is bulkier, heavier and more expensive battery packs with unfavourable trade-offs [47]. The present battery technology enables only a relatively short mileage per full charge, which is unsuitable for long distance trips due to unavailability of nationwide recharge stands [20]. A higher energy density battery packs are not only more expensive, they are also heavier which adds to the vehicle mass. In addition, recharging of the battery is time consuming in contrast to the shorter time required for refuelling which could pose as an inconvenience at times of emergencies. Another issue related to EVs is the sizing of the components which must be match the maximum vehicle rated output power that adds to the cost and weight of the vehicle [9]. However, despite the technology bottlenecking the viability of EVs, there are a number of models already available on the market, offered in a spectrum of price range. The lower priced models are commonly small, compact and lightweight to allow for the installation of a smaller EM and ESS just enough for short distance travels within the local area, whereas the premiums offer greater mileage as expected from their higher price. There is no doubt that the EV technology is advancing at a steady rate and will be the force to be reckoned with in the future but given its present glaring shortcomings, the anticipated day when all vehicles are fossil fuel-free is still a couple of decades ahead. For instance, the technology itself still needs to improve its consumers’ perceptions and expectations which are strongly influenced by mileage and price [46,48]. A mass adoption for EVs might involves a nationwide overhaul on electrical distribution channels to accommodate for the increase in numbers of recharging stations required which will definitely come at a tremendous cost. There are also expected changes in grid power demand profile as the penetration of EVs increases. Currently, EVs are only suitable for urban driving because most countries still do not have proper charging stations broadly available [33]. HEVs are regarded as a step in the right direction towards cleaner and greener vehicles. It has responded soundly to stringent policies regarding greenhouse gas emissions imposed by governments and environmental agencies around the world. The general idea of HEV is to have the best of both worlds. It provides exceptional mileage for consumer satisfaction while having a smaller tailpipe emission footprint [46,48]. These are made possible with a smaller ICE that operates at its most efficient region most of the time and can be turned ON/OFF depending on the vehicle operating condition and driver’s torque demand [9,34]. In certain driving conditions, propulsion could rely solely on EM for zero emission drive. Under mild braking, HEVs are also capable of recapturing kinetic energy, transforming it into electrical energy and storing it in the ESS. This process is known as regenerative braking. The kinetic energy during braking is usually just dissipated as heat in conventional vehicles [9,34]. Unlike FCV, HEV is a proven concept that is already possible with the current level of technology. It is ready for deployment and it does not have to wait for years to come to fruition. It serves as the perfect provisional solution to practical, yet economically viable emission free vehicles. It is also more compelling to the

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prospective buyers because they do not have the apprehension of their vehicle stalling in the middle of nowhere when there is no charging station especially when driving in suburban or rural areas. This is a huge advantage that HEVs have over pure EVs at the moment [46]. A typical HEV operates in CS mode. In this mode, the main focus of the EMS is not only to achieve the optimum fuel consumption but also to sustain the SoC of the ESS and ensure that it does not fall below the lower threshold level. This is important to avoid the ESS from being over-discharged and subsequently damaging it. Based on the driver’s input, the vehicle’s operating point is decided depending on the SoC of its ESS [10,34]. Vehicle’s operating point refers to the ratio of torque supplied from the ICE and EM based on the total amount of torque requested by the driver. In terms of design, there is no standard blueprint on how to design a HEV. HEVs come in many variations that are diverse in their configurations and sizing but their objectives remain the same – to achieve the best fuel economy and lowest possible tailpipe emission. However, HEVs are generally grouped into three big categories based on their configurations, namely series, parallel and power-split series-parallel [8,9]. The dissimilarity that separates HEV into these categories lies in the design of the power flow from the sources of energy, i.e. the fuel and ESS, to the transmission. Power flow in series HEV is passed down to the transmission only over a single path as illustrated in Fig. 2 [9]. The ICE will turn the generator to generate electricity which will be stored in the ESS. The ESS supplies the energy to the EM that powers the propulsion of the vehicle. In this configuration, the ICE is not connected directly to the transmission. The advantage of this configuration is the ICE can always operate at its highest efficiency for the best fuel consumption. This configuration shares the similar downside with pure EV where the installed EM must match the rated maximum vehicle power because the EM is the sole provider to the propulsion of the vehicle [8,9,36]. Parallel HEVs allow power flow through two paths from the energy sources to the transmission. As per Fig. 3, the ICE and EM are both connected directly to the transmission through their respective paths. The path from the ICE is called the mechanical path and the one from the ESS is the electrical path [9]. The electrical path allows for power flow in both directions. When the SoC of the battery is at high, the vehicle can be driven by both the ICE and EM together or by either of them independently given a specific operating condition. At the time of low SoC, some torque from the ICE will be diverted to turn the EM which will now functions as a generator to recharge the battery pack. The biggest merit of this design is the flexibility in choosing the size of the ESS and EM to be mounted because the maximum torque of the vehicle will be supplied in consolidation with the ICE [9,36]. However, a more complex control mechanism is required to manage the torque from both sources. By design, parallel HEVs are not suited well for frequent stop and go traffic as in typical urban driving conditions. This is due to the unavailability of charging mechanism when the vehicle is not moving. The third HEV category is the design assimilation of the previous two categories put together in single package. Fig. 4 illustrates the power-split series-parallel HEV configuration [9].

Fig. 2. Series HEV configuration.

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Fig. 3. Parallel HEV configuration.

Fig. 4. Power split series-parallel HEV configuration.

At a glance, the configuration looks similar to that of a parallel HEV. It can be perceived as a parallel HEV with a small series HEV architecture built into the design [9]. This combined configuration boasts the advantages of both series and parallel HEV to eradicate their disadvantages. For instance, the sizing issue of the ESS and EM in series HEVs is eliminated because the fundamental design principal adopted here is of the parallel HEV. On the other hand, the issue of frequent stop and go driving condition unfavourable to parallel HEVs is also solved with the ability to charge the battery even when the vehicle is stationary. All these are made possible by the presence of a power split device such as the planetary gear set equipped in the Toyota Prius [8,9,36]. Due to these features, seriesparallel HEV has been the choice of many car makers in recent years [36]. The main objective in the development of HEVs is to reduce fuel consumption and tailpipe emission. However, trying to achieve these ultimate goals alone is meaningless if vehicle performance and drivability are not taken into account. After all, these are the most demanded features that could sway potential customers away if it is not done right. Here is where an efficient EMS plays its role as the deciding factor on how a HEV will perform and achieve its objectives, usually by determining the optimal tradeoffs between these competing interests [10]. EMS design for HEV has come a long way since the early years of HEV development. In this paper, several EMS from recent years are separated into subcategories and reviewed which will hopefully become the foundation for the process of designing the state-of-the-art EMS suitable for the proposed TtR HEV. The core for EMS developments is established on several general rule-of-thumbs, comprising the optimization in the operation of both ICE and electrical drivetrain of HEVs. On top of being downsized in comparison to the other conventional vehicles in its class, the ICE side of HEVs has gone through a number of innovations such as; (i) they are set to operate at their most efficient region for the majority of the time to give a significant headroom advantage in terms of fuel consumption thus resulting in lower tailpipe emission, (ii) minimization of engine dynamics by the reduction of fluctuating operating points through regulations of the ICE operating speed, (iii) reduction of idle time to minimize unnecessary fuel burning, and (iv) ON/OFF times optimization to fully take advantage of the dual power sources [8]. On the electrical drivetrain side, the basics in achieving the objectives of HEV depends on; (i) the rations of battery SoC both to prolong the battery life and to allow the EM to work efficiently when needed, (ii) optimization in the EM’s operating point based on the preferred region on the torque-speed plane, and (iii) intensification of

regenerative braking to maximize energy regeneration based on driver’s behaviour [8]. In this paper, nine recent proposals on various EMS were selected from the ScienceDirect and IEEExplore databases and categorized into online and offline category. The Author took the liberty to extract their contributions along with their selected methods on handling the fuel consumption, emission and drivability problems. The earliest method of EMS for HEVs used the simple rulebased concept. Vehicle operating points are dictated based on a certain set of rules that may consist of several parameters such as vehicle or engine speed and driver’s torque demand. The advantages of the rule-based EMS are their low cost, simplicity in execution due to small computational requirement and the ability to perform in real-time. Although it does keep up to the task, the resultant performance is usually far from optimum and leaves a lot to be desired due to the inflexibility of the pre-defined rules [10]. Researchers have adopted fuzzy-logic methods to enhance the performance of rule-based EMS [13,49,50]. Fuzzy logic-based controllers use decision-making based on look-up tables to compensate for inexact measurements. This contributes to a wider range of operating point selection allowing for a more efficient operation of the EMS. They are more robust in nature and are easily tuneable to include an assortment of parameters and variables for a desired performance target [10]. Real-time or online EMS has its benefits of being easy to implement and are capable of reacting to the sudden changes in driving conditions or HEV operating environments. Here are some of the most recent online EMS approaches. 2.1. Online energy management strategy Huang et al. proposed an intelligent multi-feature statistical approach that is able to distinguish different driving conditions to create multiple sub-models that are used to select the best control strategy [11]. This model boasts fast and accurate computation and is able discriminate the conditions in real-time. With the help of machine learning, the proposed system is able to collect driving data and mine multiple features that have significant impact to the HEV performance. The process runs throughout the HEV operation mode and dynamically selects the best control option corresponding to the driving condition that yields the best performance [11]. Another method proposed by Murphey et al. uses intelligent energy controllers that are trained with machine learning framework [16]. These controllers are able to formulate the best ratio of engine power and battery power in real-time to minimize the fuel consumption while satisfying the driver's demand and system constraints [16]. Optimal power split results with multiple initial SoC and single ending points obtained from a dynamic programming optimization algorithm are used to train the controller for the best result [16]. EMS determines the amounts of energy generated, stored and consumed in every single powertrain components. The approach by Di Cairano et al. focuses on the improvement of the powertrain efficiency using online EMS controller [17]. The method applied involves the use of the energy stored in the ESS not only for operating the EM but also to help smoothen the engine transients that results from the switching between different operating points in a series HEV. This is made possible with the assist of model predictive control (MPC) algorithm integrated in the heart of the engine control unit [17]. MPC is an effective scheme to control a system that is subjected by input and limitations where the right balance between the competing control objectives is crucial to the performance of the system [17,18]. Driver’s behaviour is a big contributing factor to the overall performance of any EMS but modelling structures of driver’s behaviour is currently still underdeveloped. This motivated Di Cairano et al. to propose another

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MPC based EMS paired with machine learning that is driver-aware [18]. It combines the on-board learning of a representative driver’s behaviour and situational-based approach for stochastic optimization using quadratic programming [18]. Driver's behaviour is a ubiquitous aspect that varies from one driver to another but the approach of stochastic model predictive control with learning (SMPCL) is to model the changes in driver’s behaviour based on the appropriate responds towards the changes in driving environment [18]. Thanks to quadratic programming the SMPCL is able to handle a larger state dimension models compared to dynamic programming while reconfiguring in real-time to act in response to the changes in driver’s behaviour [18]. Zhang et al. proposed a multi-objective approach using instantaneous cost functions deployed in a parallel HEV that uses varying-domain method to dynamically switch the priority of the objectives depending on current vehicle state [19]. The multi-objective problem is transformed into non-linear programming problem and genetic algorithm (GA) is used to find the subsequent optimal solution [19]. The only drawback of rule-based and fuzzy logic-based EMS is that they are not optimized for a specific drive cycle. HEVs could perform at a higher level of efficiency if a full knowledge of the driving conditions is obtained and synthesized beforehand [14]. The idea is to extract as many important features and information that may influence the performance of a HEV as possible, to generate a global optimal solution specifically for the selected drive cycle [14]. These features and information range from traffic conditions to geographical data down to the specific driver torque demand for the entire journey. Data regarding the trip can be obtained using various modern tools such as Global Positioning System (GPS), Geographical Information System (GIS), Intelligent Traffic System (ITS) and historical driving data. These abundance of information are used to derive the global optimal solution for a specific drive cycle. The most commonly used technique is dynamic programming [12,51,52]. The downside of optimization through dynamic programming is the heavy burden of calculation that is time consuming which makes it almost impossible to be deployed as an online controller. In addition, due to heavy reliance on future information, global optimal results obtained from dynamic programming are usually not the reflection of the HEV performance in real life. They are usually used as benchmarks for EMS development for best possible outcome [13]. However, results obtained from dynamic programming and its properties have led to the derivation of various other methods of EMS. For example, global optimal solution from dynamic programming is always used as the material for machine learning and neural network training [30,53]. EMS that use dynamic programming and its equivalents that rely on future information are known as optimization-based EMS and this type of EMS controllers is usually deployed off-line to give room for more intense calculations to take place. Recent examples of off-line controllers are listed below. 2.2. Off-line energy management strategy Zhang et al. presented an EMS using fuzzy multi-objective optimization for parallel HEVs [13]. The approach taken here is by converting the energy consumption of the EM into the equivalent fuel consumption. Consequently, the whole fuel economy and emission problems are treated as optimization goals [13]. The optimization algorithm will then simulate the total fuel consumption and emission for the designated trip. Based on the optimal solution, a portion from the fuel consumption figure will be translated back into equivalent electrical energy in accordance to the available SoC allowance to achieve overall better fuel economy compared to rule-based and fuzzy logic-based controllers [13]. The next proposed method by Borhan et al. introduced a second EM/generator through a torque coupler connected

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to the vehicle driveline, providing two degrees-of-freedom for EMS operation [14]. MPC method is used with a new approximate cost-to-go function that corresponds to the deviation in the SoC, embedded into the fuel minimization problem [14]. The EMS is divided into supervisory and low level controllers respectively to compromise the complexity of the problem, each controlling their own set of parameters [14]. As a non-linear MPC-based controller, each sampling time will take account for current system state and torque demand prediction appropriate to current vehicle speed over a predicted horizon [14]. The optimal power-split ratio is decided upon these predicted states to form an EMS that is both systematic and highly predictive in nature. Samanta et al. proposed an EMS designed as an optimization problem that uses particle swarm optimization (PSO) and some of its hybrids to find the global optimal result [15]. This method is the first known application of PSO in EMS design and is currently limited to off-line implementation due to the time-consuming nature of PSO but the method is said to be applicable to HEV, PHEV and also EV [15]. Keulen et al. presented a numerical solution algorithm that rephrases constrained optimal control problem into a sequence of unconstrained counterpart [52]. The algorithm is able to calculate the global optimal power-split curve with a magnitude of calculations lesser than required by dynamic programming for the similar pre-defined power and velocity target [52]. Although the result from the numerical solution is a mere approximate equivalent of the original problem, with the appropriate grid size of quantization, the proposed method exhibits superior accuracy compared to dynamic programming [52]. The previous review on online and offline EMS for HEV selected from recent publications can be summarized as in Table 1. Up to this point, it is acknowledged that the overall performance of the deployed EMS in HEVs is heavily influenced by not only their configuration of choice but also their approach towards the EMS design itself. Some methods have been shown to showcase vast improvements in fuel consumption and tailpipe emission, but they are almost always developed around a certain configuration and most probably will not exhibit the same level of performance if alterations are to be made within its given working environment. These alterations may consist of the change in types and sizing of components, modification to the configurations and most importantly, the whimsical real-time driving conditions and driving behaviours that are infinitely varied [39]. However, this actually serves as a huge motivation for researchers to keep moving forward to further improve HEV performance based on their own perspective of the problem. There is also another factor that has to be taken into consideration during EMS development which is the level of hybridisation of the said HEV. HEVs can be classified from mild to strong class depending on the downsizing of the ICE as opposed to the upsizing of the electrical powertrain [9,44]. Mild hybrid has smaller electrical powertrain, usually incapable to propel the vehicle independently. The electrical powertrain only acts in assisting the ICE for a small injection of torque. The ICE is the main source of torque and operates as in conventional vehicles most of the time and could be turned OFF only temporarily during a short stop and go, under braking or coasting [44]. The implementation is low cost and simpler while providing high level of vehicle performance but the fuel economy and emission are almost indifferent to conventional vehicles. On the other hand, most HEVs available on the market nowadays fall under the strong hybrid class with their electrical drivetrain sized moderately enough to offer significantly better fuel economy and emission [44]. However, there is a limit on how far the level of hybridisation is allowed to be stretched due to the concern of ending up with an electrical powertrain so big and heavy that it will affect the overall performance of the vehicle. However, this next revolution in HEV

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Table 1 Summary on recent EMS for HEV. References

Modelling approach

Major findings

Huang et al. [11]

Statistical analysis and machine learning with Neural Network (Parallel HEV) Machine learning framework using optimal solution from dynamic programming (Series– Parallel HEV)

i. Automatically discriminates driving condition in real-time. ii. Fast computation time for online implementation i. Three online intelligent energy controller was proposed ii. High performance regardless of initial SoC value iii. Increased fuel saving ranging between 5%-19% depending on roadway type and congestion level i. Improved powertrain efficiency by regulating engine transients ii. Low computational burden for online implementation iii. Improved fuel consumption over rule-based EMS i. Driver-aware energy management controller ii. Quadratic programming handles larger state dimension models while reconfiguring in real-time depending on changes in driver’s behaviour i. Varying-domain method used to switch priority of objectives based on current vehicle state ii. Flexible EMS over different driving condition. i. Optimization algorithm simulated total fuel consumption treated as optimization goal. ii. A portion of simulated fuel consumption translated over to equivalent electrical energy based on available SoC iii. Improved fuel consumption over rule-based and fuzzy logicbased EMS i. Introduction of a second EM/generator for added degrees-offreedom ii. EMS division into supervisory and low level controllers iii. Systematic and highly predictive EMS i. First known PSO application in HEV ii. Optimization problem applicable across HEV, PHEV and also EV. i. Global optimal power-split curve calculation with lesser computational requirement compared to dynamic programming ii. Highly accurate equivalent approximation of optimization compared to dynamic programming

Murphey et al. [16]

Di Cairano et al. [17]

Model predictive control with power smoothing algorithm(Series HEV)

Di Cairano et al. [18]

Stochastic model predictive control and machine learning with quadratic programming (Series HEV)

Zhang et al. [19]

Multi-objective non-linear programming and Genetic Algorithm (Parallel HEV)

Zhang et al. [13]

Fuzzy multi-objective optimization (Parallel HEV)

Borhan et al. [14]

Non-linear model predictive control(Series– Parallel HEV)

Samanta et al. [15] Particle swarm optimization (Series–Parallel HEV) Keulen et al. [52] Numerical solution algoritm (Parallel HEV)

technology has allowed the level of hybridisation well beyond the strong class of HEVs. It is the succeeding step towards fully emission-free vehicles, allowing connection to the grid and it is called the PHEV.

3. Plug-in HEV (PHEV) influence PHEV is the most recent breakthrough in HEV development that has taken the world by storm. It is perceived as a step closer to truly emission-free vehicles, enhancing the current advantages of HEV by reintroducing the most desired feature of pure EV on top of it. This feature is the ability to drive using the all-electric mode for the first few kilometres for a totally fuel and emission free drive [33,34]. Unlike conventional HEVs, PHEVs allow its ESS to be charged using the outlets from the grids. The main alteration in design that differentiates a PHEV than a conventional HEV is the electrical drivetrain that serves as the primary source of energy and traction [9,20]. When fully charged, PHEVs can be driven exclusively using the energy stored in the ESS for a certain distance before it switches to the normal HEV mode to replenish the SoC of the battery [9,20,33]. This all-electric drive range is known as the AER and it depends on the size of the on-board ESS. It is a significant augmentation from the conventional concept as HEV users will now be able to have 100% emission free vehicles if they are driving within the AER most of the time, given that their vehicles are fully charged before each trip [20,33]. They also do not have the qualms of their vehicles running out of charge during long distance driving because a PHEV operates just like a normal HEV when its AER is exceeded [46,39]. This is proven to be an instrumental feature and a huge selling point for PHEVs that can help further accelerate the degree of adoption of green vehicles [48].

Online energy management strategy

Offline energy management strategy

The intervention of PHEVs into the HEV scene has brought a new dimension to EMS design philosophy. Conventional HEVs only permit operation in CS mode but PHEVs allow CD mode operation on top of CS mode [20,39]. The main issue in CS mode operation in conventional HEVs is the small margin of SoC that the EMS can fully take advantage of. This is because the SoC preservation is done using the on-board charging mechanism powered by the ICE by burning precious fuel from the tank. Consuming available portion of fuel to fully charge the ESS is seen as a counterproductive measure because it leads to higher fuel consumption and resulting in lower EMS efficiency. As prevention, existing EMS approaches allow only a minor diversion of torque from the ICE to be used, enough to sustain the SoC of the battery, not fully charging it. That is why it is very important to harvest as much energy as possible with regenerative braking to help charge the ESS. PHEVs offer a solution to this problem by replacing the substantial amount of fuel that would have been used to fully charge the battery with energy source from the grid [33]. Not only this provides a wider window of SoC for an optimum EMS operation, it also opens up a whole new level of flexibility for the design of the EMS itself. Although this added layer of flexibility has made the EMS design more complex, it is worth the extra efforts because the AER of PHEVs greatly improves fuel economy and consequently tones down tailpipe emission even further [20,33,39]. In this paper, EMS for PHEVs from recent years are reviewed. The influence of the external charging capability and AER value on EMS design, which are better suited for PHEVs are also included into consideration. Being rechargeable using the socket outlet from the grid does not change the fact that PHEVs are fundamentally just HEVs with oversized electrical drivetrain. Therefore, aside from the addition of AER into consideration, it is just logical to expect that the evolution of EMS design for PHEVs will be minimal from conventional HEVs.

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Although this might be true to some extent where there are methods proposed for PHEVs that are basically expansions of EMS for conventional HEVs, the extra room of flexibility granted by the plug-in charging has spun several other methods previously not incorporated in EMS design for conventional HEVs [39]. Some of these fresher techniques that will be discussed shortly are the results of the ability to use deep discharge batteries as ESS in PHEVs [20,33]. Deep discharge batteries differ from conventional batteries in their capability to be discharged deeper without being damaged. This is a huge feat as deep discharge batteries are impractical in conventional HEVs due to being limited to on-board charging and deep discharge batteries usually have lower charging efficiency which will greatly affect the HEV performance [33]. With PHEVs, this could be twisted as an advantage that will allow for larger portion of the battery charge to be usable by the EMS resulting in greater AER. As far as hardware level modification is concerned, there are still several other techniques that can be applied in PHEV design consideration that will further enhance its potential but they will not be discussed further in this paper[54–59]. Some of the most recent approaches that mimic the EMS for conventional HEVs impose no significant changes to the hierarchy of the primary energy source for the vehicle, which means they still treat the ICE as the main source of propulsion. The EM only exclusively drive the car under a certain speed threshold which is now higher than that of conventional HEVs, thanks to the bigger electrical drivetrain [20]. Another example is using the engine ON/ OFF control to only shut off the ICE when the speed of the vehicle is less than the electrical launch speed and during negative torque demand [20]. There are also similar contribution using optimization approach via stochastic dynamic programming that optimizes its operation based on multiple drive cycles to ration SoC by mixing the torque from both ICE and EM. This, results in blended CD mode operation that optimizes ICE operating point and minimize CS mode operation time once the SoC has reached the determined low value which takes significantly longer than the AER focused EMS [24]. The next EMS approach utilizes analytical method designed around blended mode operation, which dictates the optimal minimum engine power is the supervisory aspect to achieve optimal fuel consumption based on a certain ESS energy depletion target [28]. Chen et al. proposed an intelligent online energy management controller that consists of two neural network modules, trained based on optimized results obtained via dynamic programming that considers trip length and duration [30]. The aim is to further improve fuel economy of PHEVs by selecting the most suitable neural network module depending on the drive cycle [30]. Similar with conventional HEVs, a priori knowledge can come a long way to further improve EMS performance. Wu G. et al. proposed a method using full knowledge of real-time vehicle position and traffic conditions [31]. The traffic conditions that are obtained with the use of intelligent transportation system is able to synthesize down to the vehicle speed projection based on a selected path, to impose a specific charge depleting control strategy for the trip to maximize fuel economy [31]. Yu et al. also propose a similar triporiented EMS that uses a feedback control system that optimize power demand distribution and power delivery split with a certain target [32]. The EMS pre-plans optimal energy consumption policy for a known trip by controlling fuel to electricity usage ratio that will be enforced for the entire trip with minimal losses [32]. Some of recent examples of EMS that take full advantage of bigger electrical drivetrain in PHEVs include blended control strategy that combines CD mode operation with ICE propulsion until the SoC reaches the low threshold point before switching to CS mode operation [20]. This method allows for smooth and steady discharging of the ESS that puts less strain on the battery and can contribute to longer battery life. The torque split between

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the ICE and EM are also more evenly distributed compared to conventional HEVs allowing for higher efficiency operation of the ICE and thanks to the initial CD mode operation, the amount of fuel used for charging the ESS is significantly less. Another example of EMS focusing on CD mode operation is deployed in companion with modern global positioning system (GPS) tracking, intelligent traffic system (ITS) and geographical information system (GIS) to accurately define current position and state of vehicle [21]. Information obtained using these devices and a pre-set destination will be used as input for an advanced traffic-flow modelling technique that will generate a unique power flow management for the defined destination so that the SoC will fall to a specific terminal value when destination is reached [21]. The accuracy of the generated power flow management is improved using historical traffic information analysed with dynamic programming algorithm [21]. Tara et al. apply fuzzy logic to define a new quantity called the battery working state (BWS) which are derived from the terminal voltage of the battery and its SoC [22]. The BWS acts as an cautionary measure to make sure the battery is safe from over discharging due to erroneous estimation of SoC and is used by the fuzzy logic based EMS instead of SoC value to decide on the power split between the ICE and EM based on the power demand from the driver [22]. While the previous EMS focuses of battery health, the approach by Stockar et al. decide the power split based on total CO2 dispersed by the utilization of vehicle either directly or indirectly [26]. Another EMS implementation for PHEVs that is notable to be listed adopts a simplified mathematical model with CD mode operation that monitors the SoC depletion under constant vehicle speed [27]. Only the total trip distance is needed for the formulation of the power flow management with the electrical drivetrain serves as the primary source of propulsion. The engine will be turned on when the demand of power exceeds a certain value [27]. This is done to limit the mechanical power output of the EM within a certain limit to allow for extended use of the power from the ESS. As revealed in this section, the introduction of PHEVs has certainly made a tremendous effect on the EMS design and more importantly the efficiency and fuel economy of HEVs by the integration of external charging using the grid. AER certainly is the decisive point on deciding between which technology suits the consumer’s needs best. For people mostly driving short distances or just within the local area, a PHEV is the undisputed option as it will provide the best fuel economy out of the two. However for those who constantly drive long distances, a PHEV might not be the best option because a conventional HEV has higher efficiency in CS mode operation compared to a PHEV due to the smaller electrical powertrain contributing to lighter overall package. HEVs and PHEVs have been discussed throughout the paper and their respective advantages and disadvantages are well documented. Both are still undergoing further developments simultaneously and there is no doubt that we will witness better implementations of EMS and higher performing HEVs coming out in the near future. However the aim of this paper is to lead the way for the TtR HEV concept, and it is hoped that the merits and demerits of the aforementioned technologies will be the underlying foundation of the next HEV technology toward its fruition into production.

4. Paving ways for TtR HEV concept A TtR HEV with IWMs is a relatively new concept in vehicular technology. As the matter of writing, there are but little materials available on breakthroughs in TtR HEV design including EMS approach fitted for such technology. This still uncharted territory appeals as a big opportunity for new discoveries waiting to be

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exploited. However, many fundamental questions that are relevant to the research area still not answered by the global research community. This paper will attempt to provide revelations to possible workarounds to the tangible limitations in TtR HEVs developments. 4.1. Design By concept, TtR HEVs fall under parallel HEV category which means, in theory, the vehicle can be driven either by the ICE or the IWMs together or independently. The only major difference between a TtR HEV and a conventional parallel HEV is in the absence of physical connection between the mechanical path and electrical path [9]. This makes the complex torque coupling device unnecessary and inherently warrants a simpler and cheaper implementation of parallel HEVs. The advantage of this configuration is the 4-wheel drive capability that provides stability to the vehicle and it also offers exceptional acceleration [9]. Another advantage of this feature is the prospect to retrofit any conventional ICE vehicles and transform them into HEVs [60,61]. The prospect of transforming current ICE vehicles into TtR HEV poise as an excellent motivation for consumers to start embracing greener vehicles at a reasonable cost considerably lower than buying a whole new vehicle. However it is not seen as an enticing prospect for car manufacturers unless radical measures and policies are imposed. The trade-off for the simpler architecture is the lower efficiency for ESS charging compared to conventional HEVs, since the extra torque needed to recharge the ESS is supplied from the ICE externally through the contact with the surface of the road and limited only when the vehicle is in motion. Even with the assist from regenerative braking, the amount of energy that can be harvested internally is significantly less than a conventional HEV. The result is a much smaller window for optimum EMS operation and reduced amount of electrical energy supply for the EM which will affect the HEV performance target. However, if PHEV design is to be adopted here, the SoC allowance will no longer be such a problem. The external charging feature will provide sufficient amount of energy for a TtR HEV to perform at its highest efficiency. Conventionally, a TtR HEV, also known as separate axle parallel HEV, is designed with an EM propelling the rear axle of the vehicle to drive the rear wheels. This configuration provides propulsion for the vehicle through two independent transmissions compared to only one in conventional HEV. The emphasis is on a big EM that is capable of an output power enough to turn the axle which will in turn, spin the wheels. This mechanism results in system loss due to the extra power needed to initialize vehicle movement and during acceleration. By taking advantage of the separate axle transmission, instead of a big EM turning the axle, smaller and highly efficient EMs are fitted in the rear wheels as IWMs to provide propulsion power directly to the wheels to lower the system loss. The smaller IWMs also have the advantage of being lighter than conventional EM giving a TtR HEV the much needed advantage in terms of the mass of the vehicle. The smaller size also means that IWMs are theoretically gentler to the ESS, coupled with PHEV architecture, will grant a longer CD mode operation. 4.2. Energy management strategy and performance The key to a successful deployment of TtR HEVs lies in the EMS design. The real performance of the EMS will remain as theoretical until the real model is constructed and simulations or experimental works are done extensively. However, hypothetically a TtR HEV is conceived as having a great potential to deliver desired level of performance. This reflection is based on the studies done on various types of HEV, their EMS implementations and the

knowledge regarding their advantages and disadvantages. The major problem is due to the unavailability of information that is only measurable in the future, such as trip distance, vehicle speed, driving behaviour, road conditions, weather, etc. An energy management controller can only determine an optimal power flow strategy if the above information of an entire future trip is available in advance. Although current technology level has allowed for very detail terrain preview and real-time traffic information updates [62], other attributes such as driver’s actions and changes in weather conditions that affect vehicle operations are unfathomable beforehand. This impossibility immediately warrants for an energy management control strategy that is independent of the future information. Currently, PHEV is the obvious route to be taken as it patches up the major drawback of the TtR HEV concept. At the same time, the external charging allows for bigger ESS with higher energy density to be fitted thanks to the reduced weight and the extra room left behind by the decision to use IWMs instead of a conventional EM. The performance of IWMs is also yet to be observed and it is important to see how they fare against a conventional EM in producing the torque required for propulsion. To put less strain on the IWMs, the preferred EMS approach would be blended CD mode operation with both ICE and IWMs driving the car simultaneously. Although this will eliminate the emission-free AER from the equation, this strategy will still be able to offer exceptional fuel consumption and most importantly a farther CD mode operation in a system with favourable advantages of having high energy density ESS and smaller IWMs to begin with. Vehicle performance or drivability is also easier to be preserved this way because the core of the vehicle operation will not be bottlenecked by any singular factor. If the vehicle operation consists of mainly short distance journeys, this will allow for a longer period between the need of recharging. There are definitely still ways available to improve the performance indicator of TtR HEVs and the potential is just as promising if not even better than conventional HEVs. Development and experimental setup is currently undergoing progress and hopefully the hypotheses can be proven and desired performance target is achievable in the near future.

5. Conclusion With the impending energy crisis due to the depletion in world fuel reserves and dwindling environmental conditions, the introduction of HEVs into the market is seen as a huge contributing factor to the lift of awareness towards environmentally friendly vehicles. It is a proven technology that is already available out there and with the steady growth in adoption rate and increased emphasis by car manufacturers, the technology is becoming more affordable and accessible than ever. HEV is the bridge that connects to the future of emission-free vehicles and steady progresses made in the field are certainly pointing in the right direction with improvements in EMS design and the embracement of PHEV technology. TtR HEV is a relatively fresh aperture in the field and is still underdeveloped. The challenges associated with the TtR HEV include lower efficiency compared to a conventional HEV and underdeveloped EMS. However, further research and understanding of the vehicle technology will hopefully eradicate those inadequacies and in turn, will increase its chances to be the configuration of choice for manufacturers and consumers alike.

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Acknowledgement This work was supported by the Fundamental Research Grant Scheme (R.J130000.7823.4F273) from the Ministry of Higher Education, Malaysia and the eScienceFund (R.J130000.7923.4S100) from the Ministry of Science, Technology and Innovation Malaysia. The authors would like to thank Md Ridzuan Md Yusof, Head of Technology & Innovation Strategy, Perusahaan Otomobil Nasional Sdn. Bhd. (PROTON) for his valuable input.

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