Design and simulation for a Series-parallel Hybrid Electric city-bus

Author(s):  
Lei Wang ◽  
Yong Zhang ◽  
Chengliang Yin ◽  
Minming Zhang
Mechanika ◽  
2020 ◽  
Vol 26 (3) ◽  
pp. 252-259
Author(s):  
Bingzhan ZHANG ◽  
Guodong ZHAO ◽  
Yong HUANG ◽  
Yaoyao NI ◽  
Mingming QIU

This paper aims at proposing an efficient energy management strategy of the series-parallel hybrid electric bus (SPHEB) by using improved genetic algorithm. Firstly, the energy management strategy based on the logical threshold value is developed. The simulation model considering the vehicle dynamic performance is established by the combination of Matlab and Cruise software. Then, an improved genetic algorithm based on adaptive crossover probability and mutation probability is proposed to solve local convergence and premature convergence. Eventually, Chinese typical city bus driving cycle and the composite driving cycle are considered to show the effectiveness of the proposed energy management strategy in terms of the fuel economy. The results indicate that the fuel consumption are improved by 5.85% and 5.01% respectively, and the parameters obtained by optimizing for the composite driving cycle are more adaptable to the driving conditions and have better economic performance in all driving scenarios.


2012 ◽  
Vol 58 (2/3/4) ◽  
pp. 348 ◽  
Author(s):  
Wen Li ◽  
Tae Kyung Lee ◽  
Zoran S. Filipi ◽  
Xiangfeng Meng ◽  
Cheng Ning Zhang

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5538
Author(s):  
Bảo-Huy Nguyễn ◽  
João Pedro F. Trovão ◽  
Ronan German ◽  
Alain Bouscayrol

Optimization-based methods are of interest for developing energy management strategies due to their high performance for hybrid electric vehicles. However, these methods are often complicated and may require strong computational efforts, which can prevent them from real-world applications. This paper proposes a novel real-time optimization-based torque distribution strategy for a parallel hybrid truck. The strategy aims to minimize the engine fuel consumption while ensuring battery charge-sustaining by using linear quadratic regulation in a closed-loop control scheme. Furthermore, by reformulating the problem, the obtained strategy does not require the information of the engine efficiency map like the previous works in literature. The obtained strategy is simple, straightforward, and therefore easy to be implemented in real-time platforms. The proposed method is evaluated via simulation by comparison to dynamic programming as a benchmark. Furthermore, the real-time ability of the proposed strategy is experimentally validated by using power hardware-in-the-loop simulation.


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