Optimal Control Strategy Based on PSO for Powertrain of Parallel Hybrid Electric Vehicle

Author(s):  
Miaohua Huang ◽  
Houyu Yu
2013 ◽  
Vol 753-755 ◽  
pp. 1659-1664
Author(s):  
Jun Yan

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.


2010 ◽  
Vol 4 (1) ◽  
pp. 224-231 ◽  
Author(s):  
Shichun Yang ◽  
Ming Li ◽  
Haoyu Weng ◽  
Bao Liu ◽  
Qiang Li ◽  
...  

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Yuan Zou ◽  
Hou Shi-jie ◽  
Li Dong-ge ◽  
Gao Wei ◽  
Xiao-song Hu

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.


2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Jing Sun ◽  
Guojing Xing ◽  
Xudong Liu ◽  
Xiaoling Fu ◽  
Chenghui Zhang

The torque coordination control during mode transition is a very important task for hybrid electric vehicle (HEV) with a clutch serving as the key enabling actuator element. Poor coordination will deteriorate the drivability of the driver and lead to excessive wearing to the clutch friction plates. In this paper, a novel torque coordination control strategy for a single-shaft parallel hybrid electric vehicle is presented to coordinate the motor torque, engine torque, and clutch torque so that the seamless mode switching can be achieved. Different to the existing model predictive control (MPC) methods, only one model predictive controller is needed and the clutch torque is taken as an optimized variable rather than a known parameter. Furthermore, the successful idea of model reference control (MRC) is also used for reference to generate the set-point signal required by MPC. The parameter sensitivity is studied for better performance of the proposed model predictive controller. The simulation results validate that the proposed novel torque coordination control strategy has less vehicle jerk, less torque interruption, and smaller clutch frictional losses, compared with the baseline method. In addition, the sensitivity and adaptiveness of the proposed novel torque coordination control strategy are evaluated.


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