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

汽车工程 ›› 2020, Vol. 42 ›› Issue (9): 1174-1182.doi: 10.19562/j.chinasae.qcgc.2020.09.005

基于地图信息和循环SVR模型的纯电动汽车续驶里程预测^*

田慧欣^1,2, 李晓宇¹, 刘芳³

1.天津工业大学电气工程与自动化学院,天津 300387;
2.天津工业大学,电工电能新技术天津重点实验室,天津 300387;
3.天津工业大学计算科学与技术学院,天津 300387

出版日期:2020-09-25 发布日期:2020-10-19
通讯作者: 田慧欣,教授,博士,E-mail:icedewl@163.com
基金资助:
*国家自然科学基金(71602143, 51607122)、天津市自然科学基金(18JCYBJC22000)、天津科技特派员项目(18JCTPJC62600)和天津市高等学校创新团队培养计划(TD13-5036)资助。

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

Tian Huixin^1,2, Li Xiaoyu¹, Liu Fang³

1. School of Electrical Engineering & Automatic, Tiangong University, Tianjin 300387;
2. Tiangong University, Key Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin 300387;
3. School of Computational Science and Technology, Tiangong University, Tianjin 300387

Online:2020-09-25 Published:2020-10-19

摘要/Abstract

摘要： 针对未来行驶工况未知导致续驶里程预测精度难以提高的现状,提出了一种基于地图信息和循环支持向量回归(SVR)模型的纯电动汽车续驶里程预测方法。该方法根据地图信息预测未来的行驶工况,并将相应的工况参数作为SVR模型的输入,计算该工况下单位里程下降值和剩余值。将这一过程反复迭代,直至SOC值归零,则SVR运行次数即为剩余续驶里程。最后利用实际行驶数据,在ADVISOR中进行仿真,结果证明该方法具有较高的续驶里程预测精度。

关键词: 纯电动汽车, 剩余续驶里程, 支持矢量回归模型, 行驶工况, 地图信息

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

田慧欣, 李晓宇, 刘芳. 基于地图信息和循环SVR模型的纯电动汽车续驶里程预测^*[J]. 汽车工程, 2020, 42(9): 1174-1182.

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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基于地图信息和循环SVR模型的纯电动汽车续驶里程预测^*

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

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