摘要
为了更准确的预测车辆的剩余里程、更合理地设计整车能量管理策略、更及时地反馈给用户精确的车辆能耗水平,需要对电动汽车能耗的算法进行研究,并分解为主要的耗能模块。本文首先基于电动汽车动力经济性模型对车辆的主要耗能模块进行划分;然后从能耗的应用场景推导其计算方法;接着从实际用户的云端数据仿真计算电动汽车的能耗;最后简述电动汽车能耗在剩余里程估算、仪表显示、增程式能源管理等领域的应用。算法关键改进点:1、采用近5km里程的电动汽车能耗估算其能耗;2、采用剔除车辆动能的方式预估能耗;3、最近里程跨越怠速状态的情况采用逐步过渡方式。分析表明,该算法对于能源管理与用户节能驾驶习惯养成具有促进作用。为了考虑算法的落地实施,对仪表、智能大屏、整车控制器、云监控平台均做了分工研究。
In order to more accurately predict the remaining mileage of vehicles,more reasonable design of vehicle energy management strategy,more timely and accurate feedback to the user vehicle energy consumption level,it is necessary to study the algorithm of electric vehicle energy consumption and decompose it into main energy consumption modules.This paper firstly divides the main energy consumption modules of electric vehicles based on the power economy model of electric vehicles;then deduces the calculation method from the application scenarios of energy consumption;then calculates the energy consumption of electric vehicles from the cloud data of actual users;finally,it briefly describes the application of energy consumption of electric vehicles in the fields of remaining mileage estimation,instrument display,extended range energy management,etc.The key points of the algorithm are as follows:1.Use the energy consumption of electric vehicles with nearly 5km mileage to estimate the instantaneous energy consumption;2.To estimate the energy consumption by excluding the kinetic energy of vehicles;3.Adopt the gradual transition mode when the nearest mileage crosses the idle state.The analysis shows that the algorithm can promote energy management and energy-saving driving habits.
作者
黄奇
吕猛
龚春忠
姜旭
吴凡
HUANG Qi;LV Meng;GONG Chun-zhong;JIANG Xu;WU Fan(Jiangxi Jiangling Group Jingma Automobile Co.,Ltd.,Nanchang 330052,China;Hozon New Energy Automobile Co.,Ltd.,Jiaxing 314000,China;China Certification Center for Automotive Products,Beijing 100044,China)
出处
《汽车科技》
2024年第6期8-16,共9页
Auto Sci-Tech
关键词
电动汽车
能量消耗量
剩余续驶里程
汽车工况
能源管理
Electric Vehicle
Energy Consumption
Remaining Driving Range
Vehicle Working Condition
Energy Management
