Control Strategy Optimization of Plug-in Hybrid Electric Vehicle Based on Actual Driving Cycle
Journal Title: 河南科技大学学报（自然科学版） - Year 2018, Vol 39, Issue 5
Abstract
In order to solve the problem that the energy saving potential of the plug-in hybrid electric vehicle was not fully exploited under the actual road conditions, 60 passenger cars were selected in a city, and driving data were collected for 3 months.The collected driving data were processed by the driving cycle construction method, which combined the partitioning around medoids clustering with Markov random model.The typical driving cycle of the passenger car was built in accordance with the traffic characteristics of the city.Based on the typical driving cycles, the ISIGHT optimization platform was introduced, and the integrated optimization algorithm was used to optimize the energy management control parameters of the whole vehicle.The results show that after optimizing the control parameters, the vehicle fuel economy is increased by 8.32% compared with that before optimization.The relative error is only 1.69% compared with the semi-physical test results, which validates the effectiveness of the optimized control strategy.
Authors and Affiliations
Jianping GAO, Dexuan REN, Jianguo XI
Keywords
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