基于地图信息和循环SVR模型的纯电动汽车续驶里程预测*

doi:10.19562/j.chinasae.qcgc.2020.09.005

Abstract

Abstract: In view of the situation that the prediction accuracy of continued driving mileage is hard to enhanced due to the unknown driving conditions in the future, a prediction method for the driving mileage of battery electric vehicle based on map information and cyclic SVR model is proposed. The method predicts the future driving conditions according to map information, and takes the corresponding parameters of working conditions as the input of SVR model to calculate the SOC decline value and the remaining SOC value of the unit mileage in that working condition. The process is iterated repeatedly until the SOC value returns to zero, then the number of SVR runs is the remaining driving range. Finally, a simulation is carried out using ADVISOR based on actual driving data, and the results show that the method has a high prediction accuracy of continued driving mileage.

Key words: battery electric vehicle, remaining mileage, SVR model, driving condition, map information

Tian Huixin, Li Xiaoyu, Liu Fang. Prediction of Continued Driving Range of Battery Electric Vehicle Based on Map Information and Cyclic SVR Model[J].Automotive Engineering, 2020, 42(9): 1174-1182.

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Prediction of Continued Driving Range of Battery Electric Vehicle Based on Map Information and Cyclic SVR Model

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