Rule Correction-based Instantaneous Optimal Energy Management Strategy for Single-shaft Parallel Hybrid Electric Bus

2014 ◽  
Vol 50 (20) ◽  
pp. 113 ◽  
Author(s):  
Shuo HUANG
Keyword(s):  
Energy Management ◽  
Management Strategy ◽  
Energy Management Strategy ◽  
Hybrid Electric Bus ◽  
Optimal Energy ◽  
Electric Bus ◽  
Parallel Hybrid ◽  
Optimal Energy Management ◽  
Hybrid Electric

Trip-oriented stochastic optimal energy management strategy for plug-in hybrid electric bus

Energy ◽  
2016 ◽  
Vol 115 ◽  
pp. 1259-1271 ◽  
Author(s):  
Yongchang Du ◽  
Yue Zhao ◽  
Qinpu Wang ◽  
Yuanbo Zhang ◽  
Huaicheng Xia
Keyword(s):  
Energy Management ◽  
Management Strategy ◽  
Energy Management Strategy ◽  
Hybrid Electric Bus ◽  
Optimal Energy ◽  
Electric Bus ◽  
Optimal Energy Management ◽  
Hybrid Electric

scholarly journals Global Optimal Energy Management Strategy Research for a Plug-In Series-Parallel Hybrid Electric Bus by Using Dynamic Programming

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Hongwen He ◽  
Henglu Tang ◽  
Ximing Wang
Keyword(s):  
Energy Management ◽  
Management Strategy ◽  
State Variables ◽  
Energy Management Strategy ◽  
Hybrid Electric Bus ◽  
Optimal Energy ◽  
Electric Bus ◽  
Optimal Energy Management ◽  
Global Optimal ◽  
Hybrid Electric

Energy management strategy influences the power performance and fuel economy of plug-in hybrid electric vehicles greatly. To explore the fuel-saving potential of a plug-in hybrid electric bus (PHEB), this paper searched the global optimal energy management strategy using dynamic programming (DP) algorithm. Firstly, the simplified backward model of the PHEB was built which is necessary for DP algorithm. Then the torque and speed of engine and the torque of motor were selected as the control variables, and the battery state of charge (SOC) was selected as the state variables. The DP solution procedure was listed, and the way was presented to find all possible control variables at every state of each stage in detail. Finally, the appropriate SOC increment is determined after quantizing the state variables, and then the optimal control of long driving distance of a specific driving cycle is replaced with the optimal control of one driving cycle, which reduces the computational time significantly and keeps the precision at the same time. The simulation results show that the fuel economy of the PEHB with the optimal energy management strategy is improved by 53.7% compared with that of the conventional bus, which can be a benchmark for the assessment of other control strategies.

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