Power Energy Management and Control Strategy Study for Extended-range Auxiliary Power Unit

Zhang, Hong; Fu, Lin; Song, Jiajian; Yang, Qiangqiang

doi:10.1016/j.egypro.2016.12.007

Cited by 6 publications

(3 citation statements)

References 4 publications

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“…Yuan et al [5] designed a dynamic programming management strategy and applied it to automobiles, obtaining better experimental results and good vehicle economy. Zhang et al [6] studied the control strategy for the optimal curve to improve the traditional power-following control strategy fuel economy. Chen et al [7] designed a range-extender car using the DP control strategy.…”

Section: Introductionmentioning

confidence: 99%

MPC-ECMS Energy Management of Extended-Range Vehicles Based on LSTM Multi-Signal Speed Prediction

Zhao

Liu

et al. 2023

Electronics

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Rule-based energy management strategies not only make little use of the efficient area of engines and generators but also need to perform better planning in the time domain. This paper proposed a multi-signal vehicle speed prediction model based on the long short-term memory (LSTM) network, improving the accuracy of vehicle speed prediction by considering multiple signals. First, various signals were collected by simulating the vehicle model, and a Pearson correlation analysis was performed on the collected multiple signals in order to improve the model’s prediction accurate, and the appropriate signal was selected as the input to the prediction model. The experimental results indicate that the prediction method greatly improves the predictive effect compared with the support vector machine (SVM) vehicle speed prediction method. Secondly, the method was combined with the model predictive control-equivalent consumption strategy (MPC-ECMS) to form a control strategy suitable for power maintenance conditions enabling the equivalent factor to be adjusted adaptively in real-time and the target state of charge (SoC) value to be set. Pontryagin minimum principle (PMP) enables the battery to calculate the range extender output power at each moment. PMP, as the core algorithm of ECMS, is a common real-time optimal control algorithm. Then, taking into account the engine’s operating characteristics, the calculated range extender power was filtered to make the engine run smoothly. Finally, hardware-in-the-loop simulation (HIL) was used to verify the model. The simulation results demonstrate that this method uses less fuel than the equivalent fuel consumption minimum strategy (ECMS) by 1.32%, 9.47% when compared to the power-following control strategy, 15.66% when compared to the SVM-MPC-ECMS, and only 3.58% different from the fuel consumption of the dynamic programming (DP) control algorithm. This shows that this energy management approach can significantly improve the overall vehicle fuel economy.

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Section: Introductionmentioning

confidence: 99%

MPC-ECMS Energy Management of Extended-Range Vehicles Based on LSTM Multi-Signal Speed Prediction

Zhao

Liu

et al. 2023

Electronics

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“…Recent research has focused on APU charging control optimization and EREV energy management [46][47][48][49][50]. For instance, some researchers discovered that rule-based methods are unsuitable for various driving patterns used in the control system; alternatively, optimal solutions are considered for Energy Management System (EMS) [31,[51][52][53].…”

Section: Introductionmentioning

confidence: 99%

Range-Anxiety Reduction Strategies for Extended-Range Electric Vehicle

Prasad

Gudipalli

2023

International Transactions on Electrical Energy Systems

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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.

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“…Literature 6 discusses the PID and fuzzy control for engine speed by the means of simulation to explore the APU coordination control processing. Literature 7 analyzes the PID and feedforward PID control methods of engine speed by simulation for purpose of optimizing PID parameters through particle swarm optimization algorithm. Generator torque control and current control are discussed by simulation in Li et al 8 and the results show that torque control is superior to current control on engine speed tracking when vehicle accelerates.…”

Section: Introductionmentioning

confidence: 99%

Optimization and realization on the coordination control strategy for auxiliary power unit of range-extended electric vehicle

Liu

Lei

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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The auxiliary power unit (APU) is a major power source of range-extended electric vehicle (R-EEV). Excellent coordination control strategy of APU has a great significance impact on improving the overall electrical control system performance of R-EEV. A coordination control strategy based on parameters adapt fuzzy-PID is proposed to ensure the dynamic and static response characteristics of the coordination control system. Firstly, the APU high precision simulation control model is built in GT-Power and Matlab-Simulink. Three coordination control strategies based on traditional PID control method are designed, namely, engine speed control model (ESCM), generator torque control model (GTCM), and APU speed-torque control model (AS-TCM). The three coordination control strategies are simulated on working conditions, which include start-up working condition, power raised working condition, and power reduced working condition. Combined with the PID control principle, the control performance and inherent limitations of three traditional PID control strategies (TPCS) are analyzed and compared. Then, according to the above simulation results of analysis and comparation, the parameters adapt fuzzy-PID control strategy (PAF-PCS) is designed and simulated. The results show that three control parameters ( kp, ki, kd) are changed in real time to ensure the flexibility and adaptability of the control system and improve the stability and robustness of control system. Finally, the results of bench test show that power responds quickly and no oscillation and fixed-point power generation works smoothly, which are basically consistent with the simulation results. Therefore, the PAF-PCS proposed in this paper has good feasibility and effectiveness.

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Power Energy Management and Control Strategy Study for Extended-range Auxiliary Power Unit

Cited by 6 publications

References 4 publications

MPC-ECMS Energy Management of Extended-Range Vehicles Based on LSTM Multi-Signal Speed Prediction

MPC-ECMS Energy Management of Extended-Range Vehicles Based on LSTM Multi-Signal Speed Prediction

Range-Anxiety Reduction Strategies for Extended-Range Electric Vehicle

Optimization and realization on the coordination control strategy for auxiliary power unit of range-extended electric vehicle

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