Extended Range Electric Vehicle Research Articles

Adaptive Equivalent Fuel Consumption Minimization Based Energy Management Strategy for Extended-Range Electric Vehicle

Unlike battery electric vehicles, extended-range electric vehicles have one more energy source, so a reasonable energy management strategy (EMS) is crucial to the fuel economy of the vehicles. In this paper, an adaptive equivalent fuel consumption minimization strategy (A-ECMS)-based energy management strategy is proposed for the extended-range electric vehicle. The equivalent fuel consumption minimization strategy (ECMS), which utilizes Pontryagin’s minimum principle (PMP), is introduced to design the EMS. Compared with other ECMS strategies, an adaptive equivalent factor algorithm, based on state of charge (SOC) feedback and a proportional–integral (PI) controller is designed to update the equivalent factor under different working conditions. Additionally, a start–stop penalty is added to the objective function to take the dynamic start–stop process of the range extender into account. As a result, under the WLTC driving cycle, the proposed strategy can achieve 6.78 L/100 km comprehensive fuel consumption, saving 6.2% and 3.4% fuel consumption compared with the conventional rule-based thermostat strategy and the power following strategy. Moreover, the proposed EMS achieves the lowest ampere-hour flux among the three EMSs, indicating its ability to improve battery life.

Investigation of a Cup-Rotor Permanent-Magnet Doubly Fed Machine for Extended-Range Electric Vehicles

This paper investigates a cup-rotor permanent-magnet doubly fed machine (CRPM-DFM) for extended-range electric vehicles (EREVs). The topology and operating principle of the powertrain system based on CRPM-DFM are introduced. Then, the mathematical model of CRPM-DFM is established and the feedback linearization control of CRPM-DFM is given to realize the decoupling control of flux and torque. Moreover, the torque characteristic of CRPM-DFM is analyzed and the load torque boundaries with sinusoidal steady-state solution of CRPM-DFM is deduced. In addition, the MTPA control is derived to improve the efficiency of CRPM-DFM, and the efficiency of CRPM-DFM regarding various operating modes is investigated. Furthermore, the speed optimization strategy of ICE is proposed to reduce fuel consumption. Finally, the driving performance and fuel economy of the powertrain system are verified by simulation.

Optimization of energy management strategy for extended range electric vehicles using multi-island genetic algorithm

This study aims to improve the fuel economy of extended range electric vehicles (EREVs) and reduce the cumulative battery workload. Energy management strategy (EMS) of EREVs has a significant impact on improving the energy efficiency, prolonging the service life of batteries, and reducing the fuel consumption. To the best knowledge of the authors, most of existing studies are aimed at optimizing fuel economy, but few researches have taken the service life of the battery into account while improving fuel economy. Our study reflects the power fluctuation range of the battery from the perspective of the battery current, and also further analyzes it from the perspective of the battery energy flow. On the premise of meeting the vehicle power requirement, matrix calculation studies are carried out on the transmission ratio and the key parameters of EMS in the cooperative operation mode of hybrid energy storage system (HESS) based on regular EMS and auxiliary power unit (APU) based on equivalent fuel consumption minimum strategy (ECMS). Via Simulink software, the corresponding vehicle EMS model is developed, and the joint simulation platform of AVL Cruise and Simulink is constructed to verify the effectiveness of the proposed EMS. In order to further tap the energy-saving potential of the proposed strategy based on HESS, the multi-island genetic algorithm is adopted. Under WLTP working condition, the global optimization is conducted with the objectives of minimizing the equivalent fuel consumption and the cumulative ampere-hour through the battery when the vehicle adopts HESS and APU & ECMS operate in concert operation mode. The correlation analysis of the optimization variables is performed. The results show that the fuel economy of the optimized operation mode under WLTP condition is increased by 4.49 %, and the cumulative ampere-hour through the battery is reduced by 11.37 %.

Research on Energy Management Strategy of Range Extender Electric Vehicle considering Temperature Effect under Different Heat Demands

In order to further improve the energy utilization of the range extender electric vehicle (REEV), the energy management strategy of the REEV under different heat demands and operating temperatures is studied. Firstly, for reducing the extra fuel consumption caused by engine operating temperature, the influence of engine lubricating oil temperature on the equivalence factor is analyzed, and a novel method is proposed, which can determine the equivalence factor by three parameters, including engine temperature, operating condition type, and battery state of charge (SOC). Secondly, to reduce the influence of frequent engine start/stop on fuel consumption, a method to establish the penalty factor based on battery SOC is proposed. Finally, the engine temperature rise law under low-temperature environment and the compressor drive mode determination method under high-temperature environment are studied according to the heat demand under different ambient temperatures. An adaptive equivalent consumption minimization strategy (ECMS) considering the effect of temperature under different heat demands is proposed on the basis of the above research. The simulation under the worldwide harmonized light vehicle test cycle (WLTC) drive cycle reveals that by using the adaptive ECMS, the vehicle operating cost is reduced by 5.69% in normal temperature environment, 0.53%-2.39% in a low-temperature environment, and 0.2%-2.01% in a high-temperature environment.

Design process and simulations for the rotor system of a high-efficiency 22 kW micro-gas-turbine range extender for electric vehicles

This paper proposes a design process for a high-efficiency micro-gas-turbine (MGT)-based range extender(RE). The study includes a conceptual system design and a detailed design of an MGT RE. This design adopts a two-spool intercooled and recuperated high-speed MGT. The study focuses on the design of a low-pressure (LP) rotor system integrated with an electric generator, where a permanent magnet synchronous generator (PMSG) with a round transversally polarized bar permanent magnet (PM) is selected as a generator type. The turbine and compressor sides of the rotor are supported by dual back-to-back angular contact ball bearings modeled using a detailed five degrees of freedom contact model. The bearing cartridge is supported by squeeze film dampers (SFDs). The SFD that supports the bearings is modeled with a linear spring and an oil-film damper. Simulation results dictate that stresses in the magnet and sleeve vary due to several design parameters, thus time-efficient simulation is strongly required for effective design optimization. Also, the results indicate that the SFD design optimization range leading to acceptable rotordynamics requirements is narrow.

Optimization of Energy Saving and Fuel-Cell Durability for Range-Extended Electric Vehicle

For a fuel cell range-extended electric vehicle (FC-REEV), the fuel cell system can work at a fixed output power point, and it has high durability. However, the differences in output power and start–stop threshold can lead to a significant difference in energy loss and degradation of power sources. Based on the thermostat control strategy (TCS), the state of charge (SOC) of the battery is stabilized within a reasonable range. To obtain the lowest hydrogen consumption rate, the vehicle’s fuel economy is considered in the evaluation function. The artificial bee colony (ABC) optimization algorithm is then used to increase the driving range, and the conventional ABC-TCS (CABC-TCS) is proposed. However, the CABC-TCS leads to many start–stop times for fuel cells. To enhance the durability of the fuel cells, a penalty factor was added to the evaluation function, and a novel optimized ABC-TCS (OABC-TCS) is proposed. Different strategies were tested under federal test procedure (FTP)-72 and worldwide light-duty test procedure (WLTC) driving cycles. The results show that, compared with TCS, the optimized driving range of OABC-TCS in FTP-72 and WLTC conditions increased almost 10.59% and 10.3%. Compared with CABC-TCS, the start–stop times of OABC-TCS in FTP-72 and WLTC conditions decreased by 27.55 and 46.47 times/h, respectively.

An advanced control strategy for engine thermal management systems with large pure time delay

Stable and precise temperature control can effectively improve the engine’s fuel consumption and emissions. An advanced engine thermal management system (AETMS) composed of electric actuators has great potential in increasing the temperature tracking control accuracy and decreasing the system energy consumption. Time-varying disturbance and pure time delay in the system make it challenging to harmoniously control multiple actuators to ensure efficient temperature tracking performance. In addition, a reasonable power distribution of the actuators is beneficial to reduce the parasitic energy consumption of the system and further improve the system efficiency. In this article, an adaptive optimization control strategy consisting of a state predictor, a disturbance estimator, an energy consumption optimization block and a state tracking controller is proposed for the temperature tracking and energy consumption optimization of AETMS. Experimental verification was performed on a range extender bench of an extended-range electric vehicle, and the results show that the system achieves high-precision temperature control and energy consumption near the theoretical optimal value under changing working conditions. The temperature steady-state error is within 0.3 oC, and the temperature adjustment time is within 100 s after the first overshoot.

Retracted: Research on Compound Braking Control Strategy of Extended-Range Electric Vehicle Based on Driving Intention Recognition.

[This retracts the article DOI: 10.1155/2022/8382873.].

Energy consumption analysis of extended-range electric vehicles with different driving cycle and different modes

Energy consumption analysis of extended-range electric vehicles with different driving cycle and different modes

Energy consumption analysis of extended-range electric vehicles with different driving cycle and different modes

Energy consumption analysis of extended-range electric vehicles with different driving cycle and different modes

Research on Energy Management Optimization of Range-Extended Electric Logistics Vehicle

To ensure a reasonable energy distribution of multiple energy sources of extended-range electric vehicles in different driving scenarios, this paper proposes an adaptive energy management strategy optimization based on different road slope information and conducts in-depth real-time applications. Aiming at the problem of searching for the best working curve of APU, the method of cubic polynomial is used to obtain the efficiency curve of the range extender under the same speed and torque distribution from the experimental efficiency curves of the engine and generator, and then the golden section method is used to calculate the best working curve of APU and Search for the best working point. Taking the equivalent fuel consumption as the fuel economy index, the improved genetic algorithm is used to optimize the parameters of the energy management strategy under different working conditions and different road gradient information. Under the C - WTVC and CHTC - HT cycle conditions, the fuel economy simulation of logistics vehicles with different road gradient information is carried out. The simulation results show that: under different conditions and different road gradient information, the automatic adaptive energy management strategy can effectively improve the fuel economy performance, control the SOC fluctuation of the power battery well, and improve the battery life.

A comprehensive study for range-extended electric vehicles from the perspectives of the technology, policy, market, and design concept

A comprehensive study for range-extended electric vehicles from the perspectives of the technology, policy, market, and design concept

A comprehensive study of range-extended electric vehicles from the perspectives of the technology, policy, market, and design concept

A comprehensive study of range-extended electric vehicles from the perspectives of the technology, policy, market, and design concept

Research on Adaptive Two-Point Energy Management Strategy and Optimization for Range-Extended Electric Vehicle

Research on Adaptive Two-Point Energy Management Strategy and Optimization for Range-Extended Electric Vehicle

A Microencapsulated Phase-Change Material Suspension-Based Integrated Thermal Management System for Extended Range Electric Vehicle

Abstract In order to improve the temperature maintenance capacity for the battery of the extended-range electric vehicle (EREV) in a low-temperature environment, a microencapsulated phase-change material suspension (MPCMS)-based integrated thermal management system (ITMS) is proposed. The working modes of the proposed ITMS are divided based on series-parallel connections of the battery thermal management system (BTMS), motor thermal management system, motor thermal management system, and auxiliary power unit (APU) thermal management system; the structural parameters of the proposed ITMS are determined by robust design, and the system performance difference between the proposed ITMS and the traditional BTMS is verified through the comparative simulation in −20 °C environment. The results show that the proposed ITMS can significantly delay the decline of battery temperature in the charge-depleting (CD) stage and can reduce the time of the positive temperature coefficient (PTC) heater being on by 27.26%, and the total time being on by 54.82%. During the charge-sustaining (CS) stage, when the PTC heater is off, the average battery temperature will increase by 15.33 °C compared with the traditional BTMS. Based on the proposed ITMS, the temperature maintenance capability for the battery can be significantly improved, and the energy consumption of the PTC heater and vehicle can be reduced by 48.12–100% and 13.44–33.58%, respectively.

Predictive Energy Management Strategy for Range-Extended Electric Vehicles Based on ITS Information and Start–Stop Optimization with Vehicle Velocity Forecast

Range-extended Electric Vehicles (REVs) have become popular due to their lack of emissions while driving in urban areas, and the elimination of range anxiety when traveling long distances with a combustion engine as the power source. The fuel consumption performance of REVs depends greatly on the energy management strategy (EMS). This article proposes a practical energy management solution for REVs based on an Adaptive Equivalent Fuel Consumption Minimization Strategy (A-ECMS), wherein the equivalent factor is dynamically optimized by the battery’s State of Charge (SoC) and traffic information provided by Intelligent Transportation Systems (ITS). Furthermore, a penalty function is incorporated with the A-ECMS strategy to achieve the quasi-optimal start–stop control of the range extender. The penalty function is designed based on more precise vehicle velocity forecasting through a nonlinear autoregressive network with exogeneous input (NARX). A model of the studied REV is established in the AVL Cruise environment and the proposed energy management strategy is set up in Matlab/Simulink. Lastly, the performance of the proposed strategy is evaluated over multiple Worldwide Light-duty Test Cycles (WLTC) and real-world driving cycles through model simulation. The simulation conditions are preset such that the range extender must be switched on to finish the planned route. Compared with the basic Charge-Depleting and Charge-Sustaining (CD-CS) strategy, the proposed A-ECMS strategy achieves a fuel-consumption benefit of up to 9%. With the implementation of range extender start–stop optimization, which is based on velocity forecasting, the fuel saving rate can be further improved by 6.7% to 18.2% compared to the base A-ECMS. The proposed strategy is energy efficient, with a simple structure, and it is intended to be implemented on the studied vehicle, which will be available on the market at the end of October 2022.

Alloy Anodes for Nonaqueous Calcium-Ion Batteries

In the search to find new battery technologies that will extend current Li-ion technology towards the high-energy density and stability required for extended-range electric vehicles and efficient grid energy storage, earth-abundant working metal ions are increasingly being investigated. Calcium ion batteries are of interest due to calcium’s wide accessibility and abundance in the earth’s crust, but present novel challenges, such as sluggish diffusion kinetics and lack of known suitable intercalation hosts. The replacing of Ca metal anodes with new alloy materials that can work reversibly in current electrolyte systems is one practical route towards realizing the high voltage and capacity of a calcium battery. This complements current research in conventional Li-ion batteries to replace the conventional graphite anode by Group IIIA and IV elements. In this work, research into new alloy designs in novel electrochemical systems for Ca batteries will be explored and evaluated alongside key issues and challenges towards commercial applications.

Research on Compound Braking Control Strategy of Extended-Range Electric Vehicle Based on Driving Intention Recognition.

To improve the braking performance and braking energy feedback rate of extended-range electric vehicles, a driving intention recognition model is established based on Markov theory with brake pedal displacement, pedal displacement change rate, and pedal force as parameters, and the validity of the model is verified by actual vehicle test data. Based on the driving intention recognition model, a compound braking control strategy for extended-range electric vehicles is established with the constraints of braking force distribution and motor and battery characteristics. Cruise and MATLAB are used for joint simulation. The simulation results show that the compound braking system of extended-range electric vehicles with the compound braking control strategy based on brake intention recognition can work stably and effectively. On the premise of ensuring braking stability and safety, the braking energy recovery efficiency can be increased by 0.36% and the recovery rate can reach 12.88%. The compound braking system can effectively recover braking energy, improve the energy utilization rate of extended-range electric vehicles, and increase driving range.

Joint routing of conventional and range-extended electric vehicles in a large metropolitan network

Range-extended electric vehicles combine the higher efficiency and environmental benefits of battery-powered electric motors with the longer mileage and autonomy of conventional internal combustion engines. This combination is particularly advantageous for time-constrained delivery routing in dense urban areas, where battery recharging along routes can be too time-consuming to economically justify the use of all-electric vehicles. However, switching from electric to conventional fossil fuel modes also results in higher costs and emissions and lower efficiency. This paper analyzes this heterogeneous vehicle routing problem and describes two solution methods: an exact branch-price-and-cut algorithm and an iterated tabu search metaheuristic. From a methodological perspective, we find that the exact algorithm consistently obtains tight lower bounds that also serve to certify the metaheuristic solutions as near-optimal. From a policy standpoint, we examine a large-scale real-world case study concerning parcel deliveries in the Chicago metropolitan area and quantify various operational metrics including energy costs and vehicle miles traveled. We find that by deploying roughly 20% of range-extended vehicles with a modest all-electric range of 33 miles, parcel distributors can save energy costs by up to 17% while incurring less than 0.5% increase in vehicle miles traveled. Increasing the range to 60 miles further reduces costs by only 4%, which can alternatively be achieved by decreasing the average service time by 1 minute or increasing driver working time by 1 hour. Our study reveals several key areas of improvement on which vehicle manufacturers, distributors, and policy makers can focus their attention.

Modeling and Simulation of Extended-Range Electric Vehicle with Control Strategy to Assess Fuel Consumption and CO2 Emission for the Expected Driving Range

Extended-Range Electric Vehicles (EREVs) are intended to improve the range of battery electric vehicles and thus eliminate drivers’ concerns about running out of energy before reaching the desired destination. This paper gives an insight into EREV’s performance operating according to the proposed control strategy over various driving cycles, including the Worldwide Harmonized Light-duty Test Cycle Class 3b (WLTC 3b), Federal Test Procedure (FTP-75), and China Light-Duty Vehicle Test Cycle (CLTC-P). Simulation runs were performed in Matlab-Simulink® for different cases of drive range, electricity mix, and vehicle mass. The control strategy goal was to aim at a specified value of battery state of charge at the targeted range value. The obtained test results included: pure electric drive range, acceleration times, EREV range tests, control strategy range errors, Range Extender (REX) utilization metric and distribution of its engagement instances, fuel consumption, total equivalent CO2 emission, powertrain efficiency, and specific energy consumption. The control strategy operated on average with a range error of −1.04% and a range mean square error of 2.13%. Fuel consumption (in range extension mode) varied between 1.37 dm3/100 km (FTP-75) and 6.85 dm3/100 km (WLTC 3b Extra-High 3). CO2eq emission was 95.3–244.2 g/km for Poland, 31.0–160.5 g/km for EU-27, and 1.2–147.6 g/km for Sweden. This paper is a valuable source of information for scientists and engineers seeking to learn the advantages and shortcomings of EREV drives with a proposed control strategy, based on various sets of results.