Extended Range Electric Vehicle Research Articles

Application-oriented mode decision for energy management of range-extended electric vehicle based on reinforcement learning

Application-oriented mode decision for energy management of range-extended electric vehicle based on reinforcement learning

Research and optimization of energy management strategies for range-extended electric vehicles

Research and optimization of energy management strategies for range-extended electric vehicles

A transfer-based reinforcement learning collaborative energy management strategy for extended-range electric buses with cabin temperature comfort consideration

Electric vehicles (EVs) have received extensive attention as an environmentally friendly and sustainable mode of transportation. To address “range anxiety” issues, extended-range electric vehicles (EREVs) have gradually gained popularity as a solution. However, current research on energy management strategies (EMS) for EVs often overlooks the energy consumption of the air conditioning (AC) system, resulting in suboptimal energy allocation. Therefore, this study focuses on the extended-range electric bus (EREbus), an extended-range electric bus, and incorporates the AC system into its EMS, enabling coordinated optimization with the powertrain system. First, the study embeds a control-oriented cabin thermal management model based on the powertrain model. Next, representations transfer-based reinforcement learning (RTRL) transfers the learned policy representations from the AC-off state to the EMS in the AC-on state. Furthermore, the study analyzes the impact of different representation transfers on powertrain performance and thermal comfort. The results demonstrate that the proposed EMS can improve the convergence rate and stability of training. Compared to direct learning methods, RTRL exhibits clear advantages in reducing operating costs and improving cabin thermal comfort, achieving reductions of 8.3%–12.6 % and 5.2%–27.0 % in operating costs for driving modes with different battery levels. Moreover, setting the transfer layer appropriately promotes the utilization of the global optimal potential of RTRL. This research provides support for energy management and holds the potential for promoting the development of EVs.

Powertrain structure analysis of extended range electric vehicles

Since its invention, the internal combustion engine has greatly contributed to the development of human civilization and is also an important symbol of the progress of human civilization. The energy and environmental problems brought by traditional automobiles have seriously restricted the development of today's automotive industry. Due to the bottleneck of pure electric vehicle power battery technology, its short range and short battery life, the extended range electric vehicle is a smooth transition model of the pure electric vehicle, with its high efficiency, small battery capacity, long driving range and other advantages have received widespread attention. In this paper, the key technical issues, including the component selection, parameter matching, and control strategy of the extended-range electric vehicle drive system, are analyzed and discussed in detail. Several issues worthy of attention in future research are pointed out in the paper and provide insights for further development of extended-range electric vehicles.

Preparation of ‘Extended Range’ thin-film nanocomposite reverse osmosis membrane with excellent permeability and selectivity

Thin-film nanocomposite (TFN) membrane possesses great potential in breaking through the ‘trade-off’ effect, in which nanomaterials are incorporated in the polyamide layer to improve the membrane structure as well as provide extra lower-resistance water channel. However, the aggregation of nanoparticles under high loading concentration always induces decline of salt rejection though higher water flux can be achieved. Inspired by the concept of ‘Extended Range Electric Vehicles’, 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) liposomes were selected as the extended range materials to make up the defects of TFN membranes that excess palygorskite (Pal) brought in present study. The results showed that 1.3 mg/ml loading concentration of Pal led to dramatic decline of NaCl rejection from 99.3 % to 96.8 % though 63.1 % flux enhancement achieved compared to thin-film composite (TFC) membranes. Incorporation of 0.008 mg/ml DOPC liposomes brought further 55.5 % flux enhancement compared to TFN-Pal1.3 membrane and total 153.6 % increment compared to TFC membranes (1.98 → 5.02 L/m2·h·bar). Most importantly, the NaCl rejection of TFN-Pal1.3-DOPC0.008 membranes reverted to 99.1 % and the flux recovery rate increased to 92 %. This study provides novel method for increasing the loading concentration of nanoparticles in the selective layer combined with better dispersion, and demonstrates the feasibility of the concept of ‘Extended Range’ TFN reverse osmosis (RO) membrane.

Adaptive Fuzzy Power Management Strategy for Extended-Range Electric Logistics Vehicles Based on Driving Pattern Recognition

The primary objective of an energy management strategy is to achieve optimal fuel economy through proper energy distribution. The adoption of a fuzzy energy management strategy is hindered due to different reasons, such as uncertainties surrounding its adaptability and sustainability compared to conventional energy control methods. To address this issue, a fuzzy energy management strategy based on long short-term memory neural network driving pattern recognition is proposed. The time-frequency characteristics of vehicle speed are obtained using the Hilbert–Huang transform method. The multi-dimensional features are composed of the time-frequency features of vehicle speed and the time-domain signals of the accelerator pedal and brake pedal. A novel driving pattern recognition approach is designed using a long short-term memory neural network. A dual-input and single-output fuzzy controller is proposed, which takes the required power of the vehicle and the state of charge of the battery as the input, and the comprehensive power of the range extender as the output. The parameters of the fuzzy controller are selected according to the category of driving pattern. The results show that the fuel consumption of the method proposed in this paper is 5.8% lower than that of the traditional fuzzy strategy, and 4.2% lower than the fuzzy strategy of the two-dimensional feature recognition model. In general, the proposed EMS can effectively improve the fuel consumption of extended-range electric vehicles.

Armature Reaction Analysis and Performance Optimization of Hybrid Excitation Starter Generator for Electric Vehicle Range Extender

The armature reaction of the hybrid excitation starter generator (HESG) under load conditions will affect the distribution of the main magnetic field and the output performance. However, using the conventional field-circuit combination method to study the armature reaction has the problem of low accuracy and inaccurate influencing factors. Therefore, this paper proposed a graphical method to analyze the armature reaction and a new type of HESG with a combined-pole permanent magnet (PM) rotor and claw-pole electromagnetic rotor. The analytical formula of the voltage regulation rate under the armature reaction was derived using the graphical method. The main influencing parameters of the armature reaction magnetic field (ARMF) were analyzed, and the overall output performance was analyzed using finite element software. On this basis, comparison analyses before and after optimization and the prototype test were carried out. The results show that the direct-axis armature reaction reactance, quadrature-axis armature reaction reactance, and voltage regulation rate of the optimized HESG were significantly reduced, the output voltage range of the whole machine was wide, and the voltage regulation performance was good.

Driving Cycle-Based Energy Management Strategy Development for Range-Extended Electric Vehicles

<div>Environmental concerns and technological progress push the development and market penetration of electric vehicles (EVs) and hybrid electric vehicles (HEVs). On the other hand, transportation systems are becoming more efficient by improved communication systems within vehicles and between vehicles and infrastructure. In this study, a driving cycle-based energy management strategy is developed for range-extended electric vehicles (REEVs) to increase system efficiency and equivalent vehicle range. A validated vehicle model is developed by critical subsystem testing and a comparative study is conducted to assess the developed strategy. The results showed that the optimized strategy can save CO<sub>2</sub> emission by 6.21%, 1.77%, and 0.58% for heavy, moderate, and light traffic, respectively. Furthermore, the efficient use of a range extender (REx), guided by traffic data, extends the vehicle range, especially in heavy traffic conditions.</div>

Optimal design of rotor structure for vibration and noise reduction in electric vehicle generator

In order to reduce the vibration noise of an extended-range electric vehicle (EREV) generator, an optimization method based on changing the rotor structure is proposed in this paper. Firstly, the specific optimization scheme is determined by theoretical and simulation analysis to perform skew pole segmentation of the rotor, while using an eccentric pole arc design to determine the optimal parameters with the target of cogging torque. Then, in order to verify the feasibility of the scheme, the main performance of the generator before and after the optimization is analyzed, including radial electromagnetic force wave, counter-electromotive force (counter EMF), electromagnetic torque, and rotor strength. Finally, a high-precision finite element model of the generator was established, the vibration acceleration, as well as the sound pressure level before and after optimization, were calculated, and a noise test was completed. The results show that the optimized scheme significantly weakened the cogging torque of the generator, while reducing the radial electromagnetic force wave and counter EMF distortion rate to a certain extent, and finally significantly improved the vibration and noise performance of the generator.

Indium Alloy as Anodes for Rechargeable Calcium Ion Batteries at Room Temperature

Rechargeable multivalent ion batteries are poised to deliver the necessary breakthroughs in energy density and stability required for extended-range electric vehicles and large-scale grid energy storage. Calcium ion batteries are of interest owing to their high theoretical energy densities, natural abundance, and safety, yet are hindered by calcium’s strong interactions with non-aqueous electrolyte solutions and a general lack of suitable intercalation hosts. In order to realize the high voltage and theoretical capacity of a calcium-ion battery, replacement of the Ca metal anode with new electrode materials that can operate reversibly in conventional electrolyte systems is necessary, beginning with fundamental studies to identify novel intercalation or alloy-type hosts which can provide high-Ca content while avoiding considerable volume expansion and capacity loss. In this work, research into a novel indium anode as a host for Ca2+ ions in conventional electrolytes at room temperature is presented.

Unlocking the multi-mode energy-saving potential of a novel integrated thermal management system for range-extended electric vehicle

The thermal management system of range-extended electric vehicles (REEV) is essential for energy saving. There is a lack of modification methods for enhancing its performance under multiple operating modes. Herein, we present a combined cooling and power cycle-based basic integrated thermal management system (ITMS) for the REEV and propose a generalised performance improvement approach adapted to multiple operating modes. Composed of a waste heat recovery and a cooling subsystem, the basic ITMS can achieve heat recovery and thermal management of the range extender's coolant and recirculated exhaust gas and cools the passenger compartment and battery packs. The factors limiting the basic ITMS are identified through parametric analysis: the low evaporative pressures constrained by the low-temperature waste heat (engine coolant) and cooling target (passenger compartment). In order to unlock the multi-mode potential of the ITMS, we introduce the liquid-vapour separation condenser to separate the working fluid (zeotropic mixture) into two mixtures with different volatility. The high-volatility mixture is utilised to absorb the low-temperature engine coolant's waste heat and generate the low-temperature cooling energy for the passenger compartment, lifting evaporative pressures while keeping the condensation pressure unchanged. Then, a multi-mode comparison verifies the modified system. When the vehicle operates with the range extender on and with/without cooling demand, the vehicle fuel consumption rate can be reduced by 6.6% and up to 12.5%, respectively. When the vehicle runs in pure electric mode and with cooling demand, the ITMS's electrical consumption can be lowered by 7.4%. Accordingly, matching the volatility of the zeotropic working fluid and the thermal management objects enables REEV's ITMS to fulfil substantial energy savings in multiple operating modes.

Analyzing the Usage of Wankel Engine Technology in Future Automotive Powertrains

<div>The Wankel engine is an eccentric rotary internal combustion engine known for its simplicity, compactness, reliability, and efficiency. However, issues related to sealing, efficiency, and emissions have hindered its widespread use. Recent advancements in sealing technology, novel designs, material coatings, and alternative fuels have addressed some of these problems, leading to improvements in Wankel engine performance. This study examines these advancements in Wankel engine technology and proposes three potential applications for future automotive use. The first application involves utilizing a Wankel engine with a continuously variable transmission to replace the powertrain in conventional vehicles. The second application suggests replacing the engine in a series-parallel electric-hybrid architecture with a Wankel engine. Lastly, the third application explores using a Wankel engine as a range extender for electric vehicles. To evaluate the benefits in terms of fuel consumption for different drive cycles, each of these applications was modeled using the Future Automotive System Technology Simulator (FASTSim). The models were assessed with both standard Wankel engines and those incorporating recent advancements. The results indicate a potential reduction in fuel consumption when utilizing improved Wankel engine designs compared to traditional piston-based engines. However, it should be noted that these improved Wankel engines still face significant challenges regarding hydrocarbon emissions. Furthermore, the study identified a promising application for Wankel engines as range extenders in electric vehicles, suggesting their potential to enhance the overall efficiency of electric transportation.</div>

Design and Simulation of the Power Transmission System of extended range electric Vehicle based on MATLAB/Simulink

With the rapid growth of automobile ownership, energy shortage and exhaust pollution have become the two major problems restricting the development of automobiles. Electric vehicles with zero fuel consumption and pollution-free advantages are the future direction of development. But battery technology is not mature at this stage, and the driving distance of electric vehicles is short. Extended range electric vehicle is a hybrid electric vehicle equipped with a range extender based on a pure electric vehicle. When the power is sufficient, the whole vehicle runs with pure electric power. When the power is insufficient, the range extender works to drive the vehicle. As a kind of electric vehicle that can extend driving range, the extended-range electric vehicle has great research significance at present. In this paper, based on MATLAB/Simulink platform, the simulation model of the vehicle power transmission system is built by using the experimental modeling method. According to the model, the dynamic performance simulation of the extended-range electric vehicle is carried out, and the rationality of parameter matching of the vehicle components is verified.

Modified Particle Swarm Optimization Based Powertrain Energy Management for Range Extended Electric Vehicle

The efficiency of hybrid electric powertrains is heavily dependent on energy and power management strategies, which are sensitive to the dynamics of the powertrain components that they use. In this study, a Modified Particle Swarm Optimization (Modified PSO) methodology, which incorporates novel concepts such as the Vector Particle concept and the Seeded Particle concept, has been developed to minimize the fuel consumption and NOx emissions for an extended-range electric vehicle (EREV). An optimization problem is formulated such that the battery state of charge (SOC) trajectory over the entire driving cycle, a vector of size 50, is to be optimized via a control lever consisting of 50 engine/generator speed points spread over the same 2 h cycle. Thus, the vector particle consisted of the battery SOC trajectory, having 50 elements, and 50 engine/generator speed points, resulting in a 100-D optimization problem. To improve the convergence of the vector particle PSO, the concept of seeding the vector particles was introduced. Additionally, further improvements were accomplished by adapting the Time-Varying Acceleration Coefficients (TVAC) PSO and Frankenstein’s PSO features to the vector particles. The MATLAB/SIMULINK platform was used to validate the developed commercial vehicle hybrid powertrain model against a similar ADVISOR powertrain model using a standard rule-based PMS algorithm. The validated model was then used for the simulation of the developed, modified PSO algorithms through a multi-objective optimization strategy using a weighted sum fitness function. Simulation results show that a fuel consumption reduction of 12% and a NOx emission reduction of 35% were achieved individually by deploying the developed algorithms. When the multi-objective optimization was applied, a simultaneous reduction of 9.4% fuel consumption and 7.9% NOx emission was achieved when compared to the baseline model with the rule-based PMS algorithm.

Development of adaptive cruising strategy of extended range electric vehicle based on driving behavior

In order to develop an efficient and humanized adaptive cruise control (ACC) system for the extended range electric vehicle (EREV), a driving behavior based novel adaptive cruising strategy is developed using ACC system and EREV co-simulation model. The virtual driving platform is constructed and virtual driving experiments for various drivers are performed to obtain the core characteristics of different driver types. The constant time headway (CTH) safety distance model based on core characteristics and car-following model based on model predictive control (MPC) algorithm are developed to meet expectations of different driver types. An adaptive cruising strategy of ACC system in EREV is developed. Specially, the vehicle drive cost is investigated while the battery life and equivalent fuel consumption are considered. It is seen from the simulation results that the ACC system can meet the requirement of different driver types. Compared with the other three control strategies, the proposed adaptive cruising strategy can effectively reduce the vehicle drive cost.

Integrated energy and thermal management strategy for extended range electric vehicle based on battery temperature and state-of-charge global planning

There is a coupling relationship between energy and thermal management of extended range electric vehicle (EREV), so developing an integrated energy and thermal management strategy (IETMS) is an effective approach to reduce fuel consumption and battery degradation and further improve vehicle driving economy. Global optimization of EREV energy and thermal management is solved by dynamic programming based on adaptive grid optimization (AGO-DP), which enhances optimization performance by narrowing the feasible domain of battery temperature and state-of-charge (SOC). Meanwhile, within the hierarchical model predictive control (MPC) framework, a novel IETMS based on battery temperature and SOC global planning is proposed in this study. According to the road and weather information, the battery temperature and SOC reference trajectories approximating to the global optimum are generated to guide real-time control. Then MPC is formulated to minimize total operating cost by coordinating APU output power and battery cooling power in the short-term prediction horizon. The simulation results show that the proposed IETMS comprehensively optimizes the vehicle economy from the aspects of tracking reference trajectory, reducing battery peak current and improving fuel efficiency. The total operating cost decreases by 1.77%–14.52% compared with other strategies. Moreover, the proposed IETMS also exhibits desirable versatility and robustness under different driving scenarios, achieving 86.60%—92.18% of the optimal performance.

Design and Performance Comparison of Novel Flux-Concentrating IPM Machines for Power Generation System Application of Extended-Range Electric Vehicle

A new spoke-type interior permanent magnet (IPM) machine with enhanced flux-concentrating capability and high saliency ratio rotor is proposed for the extended-range electric vehicles traction applications. The evolution of the proposed flux-concentrating rotor structure from the spoke-type IPM rotor is illustrated to achieve a higher saliency ratio and higher air-gap flux density. Two IPM motors with the same magnets volume are developed and compared with the proposed IPM machine. The rotor configurations are optimized by the multiobjective genetic algorithm to maximize the torque/power and minimize the cogging torque, as well as increasing the saliency ratio. Furthermore, the major electromagnetic performance of the three machines are analyzed and compared by the finite-element analysis (FEA), including the air-gap flux density, cogging torque, saliency ratio, torque-current curves, and field-weakening capability. The results show that the IPM machine with high saliency ratio rotor can achieve higher torque/power, maximum torque per ampere capability, and flux-weakening ability. Finally, a-rated 60-kW PM motor with the proposed rotor is manufactured and experimented to verify the results of the FEA.

Range-Anxiety Reduction Strategies for Extended-Range Electric Vehicle

Transportation is the leading source of logistics, and people contribute the significant primary emissions for increasing global warming, so we should avoid such a situation and concentrate on zero emissions. The range of the vehicle is the major problem (range-anxiety) in electric vehicles. Nowadays, researchers focus on range extender optimization since range extenders significantly improve the range of the vehicle with an auxiliary power unit (APU), which can prove consumer satisfaction. However, range extenders can recover energy by proposing the various configurations and systems of extended-range electric vehicles (EREV). Many industries and researchers summarize these efforts to optimize and find the solution for range-extenders. This paper reviewed the most suitable technologies for energy recovery and state-of-the-art topological constructions. The analysis of the study primarily concentrated on optimizing the cost of the systems, fewer emissions, and more fuel economy. The research is based on the range-extenders evaluation and summary for electric vehicles to guide automakers and researchers to invent other state-of-the-art configurations and topologies to obtain optimized EV ranges, namely, enhanced functionality and fewer emissions. A survey on specific extend-range electric vehicles and classification of EREV technologies, the performance of APUs, different control strategies of energy management in EREVs, and various existing difficulties are discussed and further enhanced for the future researcher EREV forecast offered by advanced technologies.

An integrated thermal management strategy for cabin and battery heating in range-extended electric vehicles under low-temperature conditions

The integrated thermal management strategy under low-temperature conditions can effectively alleviate mileage anxiety associated with electric vehicles and improve the thermal comfort of the cabin. In this study, an integrated thermal management topology for range-extended electric vehicles is proposed, which recovers the waste heat from the range extender and the electric drive system for the heating of the battery and the cabin to improve energy utilization. Considering the driving modes and heating demands, the working modes and switching rules are designed. Especially, a control-oriented coupling system model is established for pure-electric mode. Taking cabin heat load demand, battery heat generation, and electric drive system heat generation as disturbances, a model predictive controller is designed for the heating power of the heater. An integrated thermal management system model verified by experiments is established in AMEsim. The initial temperature of the environment and vehicle is −20 °C, and the target temperatures of the cabin and the battery are set at 20 °C and 25 °C respectively. The feasibility of the strategy is verified by the co-simulation of Simulink and AMEsim under 4 WLTC cycles. The results show that in the range-extended mode, the integrated system shortens the battery heating time and reduces fuel consumption by more than 10.2 % compared with the independent system. In pure-electric mode, the heating speed of the proposed model predictive control strategy is slightly faster than that of the on–off strategy, the heating energy consumption is reduced by 20.95 %, and the total energy consumption for propulsion and thermal management decreased by 2.84 %.

Research on Range Extended Electric Vehicle Based on Cruise

Recently, extended-range electric vehicles are a new solution to energy shortage and environmental pollution, which effectively increases the range of electric vehicles, extends the battery life, and reduces fuel consumption. Therefore, this paper mainly focuses on the design of the EREV powertrain, building a vehicle model by using AVL CRUISE to simulate and verify the calculated parameters of the design.Analyzing the structural characteristics of the extended-range electric vehicle and determining the vehicle’s basic parameters and performance indexes using the Aratou Free 4WD hybrid as the prototype were the first part. In this part, the drive motor on the power system, battery, and range extender were selected based on the calculated parameters. The AC asynchronous motor, ternary lithium battery, and four-stroke gasoline engine were chosen as the components of the power system in the EREV. Building the vehicle model by using the AVL Cruise and developing the calculation tasks such as cyclic driving conditions, steady-state driving performance analysis, full-load acceleration performance calculation, and hill-climbing performance analysis were the second part. After the above steps, the simulation results analysis report showed that the powertrain design meets the target and potential of electric vehicle development. This paper provides a reference for comparing the dynamic property and economy of the extended-range electric vehicle with traditional fuel vehicles.