Extended Range Electric Vehicle Research Articles

Hardware-in-the-Loop Implementation of an Optimized Energy Management Strategy for Range-Extended Electric Trucks

The reliance of the commercial transportation industry on fossil fuels has long contributed to pollutant and greenhouse gas emissions. Since full electrification of medium- and heavy-duty vehicles faces limitations due to the large battery capacity required for extended driving ranges, this study explores a Range-Extended Electric Vehicle (REEV) for medium-duty Class 6 pick-up and delivery trucks. This hybrid architecture combines an electric powertrain with an internal combustion engine range-extender. Maximizing the efficiency of REEVs requires an Energy Management Strategy (EMS) to optimally split the power between the two power sources. In this work, a hierarchical EMS is developed through model-based design and validated via Hardware-In-The-Loop (HIL) simulations. The proposed EMS demonstrated a 7% reduction in fuel consumption compared to a baseline control strategy, while maintaining emissions and engine start frequency comparable to a benchmark globally optimal EMS obtained with dynamic programming. Furthermore, HIL results confirmed the strategy’s real-time implementation feasibility, highlighting the practical viability of the controller. This research underscores the potential of REEVs in significantly reducing emissions and fuel consumption, as well as providing a sustainable alternative for medium-duty truck applications.

Energy management strategy for extended range electric logistics vehicle based on type-2 fuzzy control

To overcome the limitations of fuzzy energy management strategy (EMS) in describing uncertainty, this paper proposes an EMS based on type-2 fuzzy (T2F), which optimizes energy consumption for extended range electric logistics vehicle (ERELV). Firstly, establish an energy consumption simulation model for ERELV. Then, an EMS based on T2F controller is designed. The strategy takes the state of charge (SOC) and the demand power as the input, and the range extender power as the output. This paper analyses the influence of T2F control strategy on the energy consumption of the ERELV, and uses the model-based design method to verify the EMS in the Hardware-in-the-loop (HIL) simulation test. The test results show that compared with the traditional fuzzy control strategy, the T2F strategy can reduce the engine’s energy loss by 12.58%. Finally, actual fuel consumption tests were conducted on the established ERELV model. By comparing the results of C-WTVC and CHTC-HT operating conditions, the model was verified to meet the research requirements of EMSs in this paper and has practical significance.

Simulation Study on Factors Affecting the Output Voltage of Extended-Range Electric Vehicle Power Batteries

The power battery configuration of an extended-range electric vehicle directly affects the overall performance of the vehicle. Optimization of the output voltage of the power battery can improve the overall power and economy of the vehicle to ensure its safe operation. Factors affecting the output voltage of power batteries under different operating conditions, such as nominal voltage and the number of series and parallel connections of the battery cells, have been studied. This study uses AVL Cruise to establish an overall model of an extended-range electric vehicle to simulate the output voltage characteristics under the different operating conditions of the NEDC (New European Driving Cycle), WLTC (World Light Vehicle Test Cycle) and CLTC (China Light Duty Vehicle Test Cycle). The influence of the output voltage of the power battery under different operating conditions is studied to ensure that the power battery can output energy with high efficiency. The operating conditions have an impact on the output voltage with an idle voltage fluctuation of the operating conditions. The nominal voltage variation and the number of series and parallel connections of the battery cells affect the frequency and time of breakdown.

Optimizing high-energy lithium-ion batteries: a review of single crystalline and polycrystalline nickel-rich layered cathode materials: performance, synthesis and modification

Layered Ni-rich Li [NixCoyMnz]O2 (NMC) and Li [NixCoyAlz]O2 (NCA) cathode materials have been used in the realm of extended-range electric vehicles, primarily because of their superior energy density, cost-effectiveness, and commendable rate capability. However, they face challenges such as structural instability, cation mixing, and surface degradation, which limit their practical application. This review comprehensively discusses the synthesis, modification, and performance optimization of nickel-rich cathodes, with a focus on single-crystal (SC) NMC cathodes. The unique properties and challenges of single-crystal nickel-rich cathodes are explored in comparison to polycrystalline (PC) cathodes, with a focus on performance-enhancing strategies such as doping and surface modification.

CO2 emission characteristics of China VI hybrid vehicles

As the ownership of hybrid vehicles soars, accurately predicting and assessing CO2 emissions become crucial. This study utilized the AVL portable emission measurement system (PEMS) to reveal the actual CO2 emission of three types of hybrid vehicles. Firstly, engine speed is a key factor influencing CO2 emissions of range-extended electric vehicle (REEV) and plug-in hybrid electric vehicle (PHEV), while vehicle specific power (VSP) affects HEV. Secondly, in terms of fuel consumption, when the battery levels of REEV and PHEV are low, their fuel consumption tends to be higher than that of HEV. Specifically, the CO₂ emission factor (the amount of CO2 emitted by a vehicle per unit distance during operation) ratios of REEV to PHEV range from 1.19 to 1.89, while the ratios of REEV to HEV are between 1.41 and 2.57. Thirdly, in terms of NOX control, HEV performed significantly worse.

Analysis of the Current Status and Prospects of Extended Range Electric Vehicle Powertrain under the Background of Carbon Peaking and Carbon Neutrality Goals

Analysis of the Current Status and Prospects of Extended Range Electric Vehicle Powertrain under the Background of Carbon Peaking and Carbon Neutrality Goals

Research on approximate optimal energy management and multi-objective optimization of connected automated range-extended electric vehicle

In order to attain the optimal allocation of energy between auxiliary power unit (APU) and battery of the connected automated range-extended electric vehicle, from a multi-scale perspective, an Approximate Optimal Energy Management Strategy (AOEMS) has been proposed. Firstly, a composite determination method was designed based on prediction and parameter identification to divide the operating condition types, which could be as an operating condition prediction and feed forward control method to determine the approximate optimal power distribution between APU and battery. This method keeps APU operating at the optimal operating point/area as much as possible without predicting the accurate vehicle speed sequence. Then, an adaptive method based on V2X information was used to adjust the key threshold parameters in real-time using a fuzzy logic controller which reduces the algorithm complexity with prediction and division of the operating conditions types, which has significantly improved the robustness and overall performance of the optimization. Finally, the simulation and experimental results thoroughly indicated that the proposed AOEMS can better balance the performances, as anticipated, enhancing economy, reducing emissions, and extending battery lifewere effectively maintained in equilibrium.

Investigation on the oscillation characteristics and performance prediction of a linear range extender: An analytical and numerical combined method

Linear range extender (LRE) system is directly coupled with free piston engine and linear motor and has great application potential in extended-range electric vehicles. In this paper, an analytical and numerical combined method was adopted to investigate the effect of key design parameters on the design and performance prediction of an LRE system. The results showed that the energy input and consumption reach a balance state, the LRE system maintains a stable steady vibration. Increasing the system load will reduce the piston operating stroke. The peak operating velocity of the piston, the average operating velocity of the piston gradually decrease, the operating frequency and the output power decreases as the load increases. When S/B is 0.8, the system output power reaches 4.5 kW, and when S/B is 1.2, the output power is only 2.2 kW. When the mover mass is 3.0 kg, the system output power reaches 3.8 kW, and when the mover mass is 8.0 kg, the output power is only 2.4 kW. When the excess air ratio increases from 0.8 to 1.2, the peak piston speed was reduced from 6.79 m/s to 6.03 m/s, the average piston operating speed was reduced from 5.30 m/s to 4.96 m/s, and the system operating frequency was reduced from 51.2 Hz to 47.96 Hz. If the LRE system wants to have stronger resistance to load fluctuations, it should choose a larger S/B ratio and a relatively larger mover mass during design. In order to pursue higher power output, the S/B and mover mass must be relatively small.

Effect of over-expansion in a cycloidal rotary engine

An over-expanded (Atkinson cycle) reciprocating internal combustion engine is a crucial component of hybrid and range-extended electric vehicles. The realization of the over-expansion cycle with high efficiency in novel power devices with a compact, simple design, such as cycloidal rotary engines, is a promising alternative. The cycloidal rotary engine is an internal combustion engine that operates four strokes without a reciprocating mechanism and valve train. The over-expansion cycle is implemented in the cycloidal rotary engine by asymmetrical intake and exhaust port arrangements, resulting in open and closure timings. This study aimed to establish inherent characteristics of the over-expansion cycle in gasoline-fueled rotary engines with spark ignition. A numerical simulation of the gas exchange and combustion process in a wide range of over-expansion ratios was conducted. It was concluded that the over-expansion cycle is realized without typical piston engine methods such as variable valve timing and multilink mechanism. The thermal conversion efficiency is a peak function of the over-expansion ratio. In the over-expansion range of 1.1–1.2, the thermal conversion efficiency of the cycloidal rotary engine increased up to 32.7–34.5%. The benefits of fuel economy and carbon oxide emission can also be achieved within the specified range of over-expansion ratio.

Development of pure hydrogen generation system based on methanol steam reforming and Pd membrane

Methanol steam reforming (MSR) has been used for in-situ hydrogen production, while hydrogen purification remains a technical challenge to limit the applications of using hydrogen for fuel cells. This study presents a pure hydrogen generation system (PHGS) by integrating MSR and hydrogen purification modules, this system enables low-temperature reforming and high-temperature purification to achieve high yield and recovery of hydrogen. To investigate the combined effects of feedstock flow rates and pressure on MSR and purification, the performance of each module and overall PHGS system were tested. The results showed that PHGS can stably produce high purity hydrogen (>99.99%) under different conditions, the synergistic effects of two modules lead to hydrogen yield exceeding the numerical sum of individual modules. At methanol feed rate of 1.00 g/min and system pressure of 5.0 bar, the pure hydrogen flow rate, CO content, pure hydrogen yield, hydrogen recovery and thermal power output were tested about 1.70 ± 0.01 L/min, 2.4 ± 0.1 ppm, 81.1 ± 0.5%, 87.6 ± 0.5% and 350 W. The PHGS can deliver up to 500 W of thermal power and is suitable for small range-extended electric vehicles. Our work on the developed PHGS can provide a significant reference for future practical applications of systems combining MSR and membrane purification.

Enhancing the Efficiency of Rotary Thermal Propulsion Systems

Transport electrification is essential for reducing CO2 emissions, and technologies such as hybrid and range-extended electric vehicles will play a crucial transitional role. Such vehicles employ an internal combustion engine for on-board chemical energy conversion. The Wankel rotary engine should be an excellent candidate for this purpose, offering a high power-to-weight ratio, simplicity, compactness, perfect balance, and low cost. Until recently, however, it has not been in production in the automotive market, due, in part, to relatively low combustion efficiency and high fuel consumption and unburnt hydrocarbon emissions, which can be traced to constraints on flame speed, an elongated combustion chamber, and relatively low compression ratios. This work used large eddy simulations to study the in-chamber flow in a peripherally ported 225cc Wankel rotary engine, providing insight into these limitations. Flow structures created during the intake phase play a key role in turbulence production but the presence of the pinch point inherent to Wankel engine combustion chambers inhibits flame propagation. Two efficiency-enhancement technologies are introduced as disruptive solutions: (i) pre-chamber jet ignition and (ii) a two-stage rotary engine. These concepts overcome the traditional efficiency limitations and show that the Wankel rotary engine design can be further enhanced for its role as a range extender in electrified vehicles.

Magnetic Field Analysis and Development of Disk Axial–Radial Hybrid Excitation Generator for Range Extenders in Extended-Range Electric Vehicles

Magnetic Field Analysis and Development of Disk Axial–Radial Hybrid Excitation Generator for Range Extenders in Extended-Range Electric Vehicles

A Multi-objective Optimization Control Strategy of a Range-Extended Electric Vehicle for the Trip Range and Road Gradient Adaption

A Multi-objective Optimization Control Strategy of a Range-Extended Electric Vehicle for the Trip Range and Road Gradient Adaption

Research on Energy Management Strategy for Extended‐Range Electric Vehicle Based on Bargaining Game

To improve the fuel economy and battery life of extended‐range electric vehicles (EREVs), an energy management strategy (EMS) based on the bargaining game (BG) is proposed. This strategy optimizes the overall economy by optimizing power allocation. First, a bargaining model for EREVs is developed. The model considers the auxiliary power unit (APU) and the battery as two parties of the game. The power allocation between the APU and the battery optimizes both the fuel consumption and the battery life. And it also improves the overall benefit of the vehicle. Second, the effect of the discount factor on the control results is analyzed to obtain the best optimization results. Finally, compared to the thermostat strategy and the dynamic programming‐based strategy, the proposed BG‐based strategy reduces fuel consumption by 27.6% and 1.4% under the World Light Vehicle Test Procedure and reduces the effective ampere‐hour fluxes by 62.7% and 14.6%. Under the China Light‐duty Vehicle Test Cycle, it reduces fuel consumption by 32.5% and 0.5% and reduces the effective ampere‐hour fluxes by 56.8% and 27.5%. The simulation results manifest the excellent performance of the proposed BG‐based EMS.

Enhancing Energy Management Strategies for Extended-Range Electric Vehicles through Deep Q-Learning and Continuous State Representation

The efficiency and dynamics of hybrid electric vehicles are inherently linked to effective energy management strategies. However, complexity is heightened due to uncertainty and variations in real driving conditions. This article introduces an innovative strategy for extended-range electric vehicles, grounded in the optimization of driving cycles, prediction of driving conditions, and predictive control through neural networks. First, the challenges of the energy management system are addressed by merging deep reinforcement learning with strongly convex objective optimization, giving rise to a pioneering method called DQL-AMSGrad. Subsequently, the DQL algorithm has been implemented, allowing temporal difference-based updates to adjust Q values to maximize the expected cumulative reward. The loss function is calculated as the mean squared error between the current estimate and the calculated target. The AMSGrad optimization method has been applied to efficiently adjust the weights of the artificial neural network. Hyperparameters such as the learning rate and discount factor have been tuned using data collected during real-world driving tests. This strategy tackles the “curse of dimensionality” and demonstrates a 30% improvement in adaptability to changing environmental conditions. With a 20%-faster convergence speed and a 15%-superior effectiveness in updating neural network weights compared to conventional approaches, it also highlights an 18% reduction in fuel consumption in a case study with the Nissan Xtrail e-POWER system, validating its practical applicability.

Study on methanol-hydrogen engine in extended-range electric vehicles

The demand for clean and efficient new vehicle models is steadily increasing. Methanol-hydrogen engines use methanol as the main fuel and can recover the heat from engine exhaust to dissociate part of methanol into hydrogen-rich syngas. The syngas is recirculated back into the engine cylinder to improve combustion. Therefore, methanol-hydrogen engines have a higher energy utilization efficiency. This paper designed a methanol-hydrogen engine system based on a Miller cycle methanol engine. Bench tests showed that combusting methanol and dissociated methanol gas together could accelerate the fuel burn rate and improve the engine’s fuel economy. At a fixed engine speed of 2500 r/min, the BSFC of the methanol-hydrogen engine was reduced up to 5.55% compared to the original methanol engine. Further, a methanol-hydrogen extended-range electric vehicle powertrain model was built in Simulink. Simulation results indicated that, under the WTLC cycle, the methanol-hydrogen engine achieved a 22.60% reduction in fuel consumption per 100 km and saved 58.89% in fuel costs compared to the conventional gasoline engine. The methanol-hydrogen engine presented potential application in the extended-range electric vehicle.

Hydrogen fuelled stepped piston engine for ultra-low emissions hybrid and range extender electric vehicles

Hydrogen fuelled stepped piston engine for ultra-low emissions hybrid and range extender electric vehicles

Hydrogen fuelled Stepped Piston Engine for Ultra-Low Emissions Hybrid and Range Extender Electric Vehicles

Hydrogen fuelled Stepped Piston Engine for Ultra-Low Emissions Hybrid and Range Extender Electric Vehicles

Unequal Thickness Flat Wire Winding-Based Eddy Current Loss Reduction for Coreless Axial Flux Permanent Magnet Synchronous Machine Adapted to Extended-Range Electric Vehicles

Unequal Thickness Flat Wire Winding-Based Eddy Current Loss Reduction for Coreless Axial Flux Permanent Magnet Synchronous Machine Adapted to Extended-Range Electric Vehicles

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