scholarly journals A Hybrid Electric Vehicle Dynamic Optimization Energy Management Strategy Based on a Compound-Structured Permanent-Magnet Motor

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2212 ◽  
Author(s):  
Qiwei Xu ◽  
Yunqi Mao ◽  
Meng Zhao ◽  
Shumei Cui
Keyword(s):  
Neural Network ◽  
Permanent Magnet ◽  
Energy Management ◽  
Dynamic Optimization ◽  
Power Loss ◽  
Management Strategy ◽  
Hybrid Electric Vehicle ◽  
Energy Management Strategy ◽  
Permanent Magnet Motor ◽  
Engine Power

A dynamic optimization energy management strategy called Hybrid Electric Vehicle Based on Compound Structured Permanent-Magnet Motor (CSPM-HEV) is investigated in this paper. CSPM-HEV has obvious advantages in power density, heat dissipation efficiency, torque performance and energy transmission efficiency. This paper describes the topology and working principle of the CSPM-HEV, and analyzes its operating mode and corresponding energy flow laws. On this basis, the relationship about the power loss of the vehicle, the CSPM transmission ratio iCSPM and the CSPM-HEV power distribution coefficient f1 were derived. According to the optimal combination of (iCSPM, f1), the engine power and speed which minimize the power loss of the vehicle, were calculated, thus realizing the instantaneous optimal control of the vehicle. In addition, in order to improve the instantaneously optimized control processing speed, a neural network controller was established. The drive axle demand power, speed and battery State of Charge (SOC), were taken as input variables. Then, the engine power and speed were taken as output variables. The simulation results show that the average speed of the instantaneous optimization strategy after BP neural network optimization is increased by 98.1%, the control effect is significant, and it has high application value.

scholarly journals Application of the Fuel-Optimal Energy Management in Design Study of a Parallel Hybrid Electric Vehicle

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Afshin Pedram Pourhashemi ◽  
S. M. Mehdi Ansarey Movahed ◽  
Masoud Shariat Panahi
Keyword(s):  
Optimal Design ◽  
Energy Management ◽  
Management Strategy ◽  
Hybrid Electric Vehicle ◽  
Performance Metrics ◽  
Design Parameters ◽  
Programming Approach ◽  
Energy Management Strategy ◽  
Dynamic Programming Approach ◽  
Dynamic Measures

In spite of occasional criticism they have attracted, hybrid vehicles (HVs) have been warmly welcomed by industry and academia alike. The key advantages of an HV, including fuel economy and environment friendliness, however, depend greatly on its energy management strategy and the way its design parameters are “tuned.” The optimal design and sizing of the HV remain a challenge for the engineering community, due to the variety of criteria and especially dynamic measures related to nature of its working conditions. This paper proposes an optimal design scheme that begins with presenting an energy management strategy based on minimum fuel consumption in finite driving cycle horizon. The strategy utilizes a dynamic programming approach and is consistent with charge sustenance. The sensitivity of the vehicle’s performance metrics to multiple design parameters is then studied using a design of experiments (DOE) methodology. The proposed scheme provides the designer with a reliable tool for investigating various design scenarios and achieving the optimal one.

Energy management strategy for HEV based on KFCM and neural network

2018 ◽  
Vol 31 (10) ◽  
pp. e4838 ◽  
Author(s):  
Yeqin Wang ◽  
Zhen Wu ◽  
Aoyun Xia ◽  
Chang Guo ◽  
Yuyan Chen ◽  
...  
Keyword(s):  
Neural Network ◽  
Energy Management ◽  
Management Strategy ◽  
Energy Management Strategy
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