scholarly journals Fuel Economy Analysis of a Series Hybrid Electric Bus with LowSpeed Shutdown Control Strategy

2014 ◽  
Vol 7 (10) ◽  
pp. 365-380
Author(s):  
Xiaogang Wu ◽  
Han Chen ◽  
Jiuyu Du ◽  
Chen Hu
2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Jun Wang ◽  
Qing-nian Wang ◽  
Peng-yu Wang ◽  
Xiao-hua Zeng

This paper presents the system modeling, control strategy design, and hardware-in-the-loop test for a series-parallel hybrid electric bus. First, the powertrain mathematical models and the system architecture were proposed. Then an adaptive ECMS is developed for the real-time control of a hybrid electric bus, which is investigated and verified in a hardware-in-the-loop simulation system. The ECMS through driving cycle recognition results in updating the equivalent charge and discharge coefficients and extracting optimized rules for real-time control. This method not only solves the problems of mode transition frequently and improves the fuel economy, but also simplifies the complexity of control strategy design and provides new design ideas for the energy management strategy and gear-shifting rules designed. Finally, the simulation results show that the proposed real-time A-ECMS can coordinate the overall hybrid electric powertrain to optimize fuel economy and sustain the battery SOC level.


2011 ◽  
Author(s):  
Laura Tribioli ◽  
Fabrizio Martini ◽  
Giovanni Pede ◽  
Carlo Villante

2013 ◽  
Vol 341-342 ◽  
pp. 924-930
Author(s):  
Jian Ping Gao ◽  
Zhen Nan Liu ◽  
Zhi Jun Guo ◽  
Yue Hui Wei

control strategy is one of the most decisive techniques in Hybrid Electric Bus (HEB) and directly influences the dynamic performance and fuel economy. For achieving the best fuel economy and keeping the battery for a long time, First, power analytic control strategy was built; then, the hybrid optimization algorithm (HOA) based on Multi-island genetic Algorithm (MIGA) and NLPQL was built by ISIGHT software. HOA is adopted in control strategy parameters of HEB optimization. The results show that the best result can be obtained in few iterative times by HOA, the calculation time was reduce by 12 hours, the fuel economy was improved by 12% and find the rules between control strategy parameters and fuel economy the balance of the battery state of charge (SOC).


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