Research on Adaptive Optimal Control Strategy of Parallel Plug-In Hybrid Electric Vehicle Based on Route Information

2021 ◽  
Vol 22 (4) ◽  
pp. 1097-1108
Author(s):  
Kangjie Liu ◽  
Jianhua Guo ◽  
Liang Chu ◽  
Yuanbin Yu
Keyword(s):  
Optimal Control ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Optimal Control Strategy ◽  
Adaptive Optimal Control ◽  
Route Information ◽  
Hybrid Electric

Multiple-Objective Optimal Control of Hybrid Electric Vehicle

2013 ◽  
Vol 753-755 ◽  
pp. 1659-1664
Author(s):  
Jun Yan
Keyword(s):  
Optimal Control ◽  
Fuel Consumption ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric Vehicles ◽  
Optimal Control Strategy ◽  
Parallel Hybrid Electric Vehicle ◽  
Hybrid Electric ◽  
Fuel Consumption And Emissions

To reduce the fuel consumption and exhaust (HC, CO) emissions of parallel hybrid electric vehicle, the control strategy of the hybrid electric vehicle is studied in this paper. First it briefly analyzes the structure and working principle of the parallel hybrid electric vehicle drive system. Then a cost function is proposed which explains the fuel consumption and emissions. According to the minimum principle the minimum of the cost function can be got, consequently, the optimal control strategy can be obtained. Furthermore, in order to verify the effectiveness of the optimal control strategy, in MATLAB environment, it establishes a dynamic simulation model for hybrid electric vehicles. Through a comparative study between the optimal control strategy on and the traditional rules control strategy, the results of experiment it reveals that the optimal control strategy can effectively reduces fuel consumption and emissions of hybrid electric vehicles.

scholarly journals Optimal Energy Control Strategy Design for a Hybrid Electric Vehicle

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Yuan Zou ◽  
Hou Shi-jie ◽  
Li Dong-ge ◽  
Gao Wei ◽  
Xiao-song Hu
Keyword(s):  
Optimal Control ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Heavy Duty ◽  
Dynamic Features ◽  
Optimal Control Strategy ◽  
Energy Control ◽  
Optimal Energy ◽  
Parallel Hybrid ◽  
Hybrid Electric

A heavy-duty parallel hybrid electric truck is modeled, and its optimal energy control is studied in this paper. The fundamental architecture of the parallel hybrid electric truck is modeled feed-forwardly, together with necessary dynamic features of subsystem or components. Dynamic programming (DP) technique is adopted to find the optimal control strategy including the gear-shifting sequence and the power split between the engine and the motor subject to a battery SOC-sustaining constraint. Improved control rules are extracted from the DP-based control solution, forming near-optimal control strategies. Simulation results demonstrate that a significant improvement on the fuel economy can be achieved in the heavy-duty vehicle cycle from the natural driving statistics.

Equivalent fuel consumption optimal control of a series hybrid electric vehicle

2009 ◽  
Vol 223 (8) ◽  
pp. 1003-1018 ◽  
Author(s):  
J-P Gao ◽  
G-M G Zhu ◽  
E G Strangas ◽  
F-C Sun
Keyword(s):  
Optimal Control ◽  
Fuel Consumption ◽  
Control Strategy ◽  
Supervisory Control ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Optimal Control Strategy ◽  
Equivalent Fuel ◽  
Hybrid Electric ◽  
Equivalent Fuel Consumption

Improvements in hybrid electric vehicle fuel economy with reduced emissions strongly depend on their supervisory control strategy. In order to develop an efficient real-time supervisory control strategy for a series hybrid electric bus, the proposed equivalent fuel consumption optimal control strategy is compared with two popular strategies, thermostat and power follower, using backward simulations in ADVISOR. For given driving cycles, global optimal solutions were also obtained using dynamic programming to provide an optimization target for comparison purposes. Comparison simulations showed that the thermostat control strategy optimizes the operation of the internal combustion engine and the power follower control strategy minimizes the battery charging and discharging operations which, hence, reduces battery power loss and extends the battery life. The equivalent fuel consumption optimal control strategy proposed in this paper provides an overall system optimization between the internal combustion engine and battery efficiencies, leading to the best fuel economy.

scholarly journals Energy Management for a Power-Split Plug-In Hybrid Electric Vehicle Based on Reinforcement Learning

2018 ◽  
Vol 8 (12) ◽  
pp. 2494 ◽  
Author(s):  
Zheng Chen ◽  
Hengjie Hu ◽  
Yitao Wu ◽  
Renxin Xiao ◽  
Jiangwei Shen ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Electric Vehicle ◽  
Energy Management ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Gasoline Engine ◽  
Energy Management Strategy ◽  
Optimal Control Strategy ◽  
Power Split ◽  
Hybrid Electric

This paper proposes an energy management strategy for a power-split plug-in hybrid electric vehicle (PHEV) based on reinforcement learning (RL). Firstly, a control-oriented power-split PHEV model is built, and then the RL method is employed based on the Markov Decision Process (MDP) to find the optimal solution according to the built model. During the strategy search, several different standard driving schedules are chosen, and the transfer probability of the power demand is derived based on the Markov chain. Accordingly, the optimal control strategy is found by the Q-learning (QL) algorithm, which can decide suitable energy allocation between the gasoline engine and the battery pack. Simulation results indicate that the RL-based control strategy could not only lessen fuel consumption under different driving cycles, but also limit the maximum discharge power of battery, compared with the charging depletion/charging sustaining (CD/CS) method and the equivalent consumption minimization strategy (ECMS).

Adaptive optimal control based on driving style recognition for plug-in hybrid electric vehicle

Energy ◽  
2019 ◽  
Vol 186 ◽  
pp. 115824 ◽  
Author(s):  
Qiuyi Guo ◽  
Zhiguo Zhao ◽  
Peihong Shen ◽  
Xiaowen Zhan ◽  
Jingwei Li
Keyword(s):  
Optimal Control ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Driving Style ◽  
Adaptive Optimal Control ◽  
Hybrid Electric
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