基于实际行驶数据的电动汽车能耗分析与预测  

Electric Vehicle Energy Consumption Analysis and Prediction Based on Real-world Driving Data

作　　者：赵敬玉 徐铖 李晓宇 ZHAO Jingyu;XU Cheng;LI Xiaoyu(School of Mechanical Engineering,Hebei University of Technology,Tianjin 300130)

机构地区：[1]河北工业大学机械工程学院,天津300130

出　　处：《机械工程学报》2023年第10期263-274,共12页Journal of Mechanical Engineering

基　　金：国家自然科学基金(52202465);河北省教育厅基金(C20220312)资助项目。

摘　　要：相比于传统燃油汽车,较短的行驶里程和较长的充电时间是电动汽车的两大技术难点,因此准确地能耗预测对于缓解驾驶者的“里程焦虑”具有重要意义。以天津市实车运行数据为样本,将车辆行驶数据划分为若干运动学片段,分析电动汽车行驶过程中对能耗影响的相关因素,包括行驶状态、运行工况对能耗的影响和制动能量回收对续驶里程的影响;以提高能耗预测模型的精度为目标,提出一种基于行驶工况类别的能耗预测方法,首先通过马尔科夫蒙特卡洛算法实现未来行驶工况曲线预测,融合神经网络算法识别出拥堵工况、城市工况和高速工况三种类别,从三类行驶工况提取出特征参数,分别输入到相应的XGBoost算法中构建能耗预测模型实现对未来行驶能耗的精准预测;该方法与传统能耗预测方法结果进行对比,结果表明所提出的方法在实际行驶条件下可以有效提高能耗预测精度。Compared with the traditional vehicles,the shorter driving mileage and longer charging time are two technology issues for electric vehicles.Hence,the accurate prediction of electric vehicle energy consumption has important significances for mitigating the driver’s“range anxiety”.Taking the actual operating of electric vehicle in Tianjin,the vehicle driving data are divided into several kinematic segments to analyze the related factors affecting the energy consumption of electric vehicles during driving period including the influence of driving state and operating condition on energy consumption and the influence of braking energy recovery on driving range.For improving the accuracy of energy consumption model,Markov chain Monte Carlo algorithm is applied to predict the curve of future driving cycle.Meanwhile,the neutral network is employed to identify the categories of driving cycles such as congestion driving cycle,city driving cycle and high-speed driving cycle.Then the significant features are extracted from the three driving cycles,respectively.The features are fed into XGBoost algorithm to construct energy consumption model for realizing accurate energy consumption prediction.The results indicate that the proposed method can effectively improve the accuracy of energy consumption compared with the traditional methods.

关 键 词：纯电动汽车 运动学片段 马尔科夫蒙特卡洛 能耗预测 

分 类 号：U469[机械工程—车辆工程]