摘要
为了对特定用户选择性价比较高的制动能量回收措施,需要对驾驶习惯对应制动能量占比较大的用户进行识别,并通过成本与收益折算选配制动能量回收方案。文章首先提出制动能量回收强度计算模型,然后通过大数据平台提取典型用户示例,接着列举常用的制动能量优化措施及其成本预估,最后按照收益大于成本的原则对各示例用户的选配方案进行选择。基于大数据对特定用户的定制化设计,将是未来汽车设计的重要方向。
In order to select cost-effective braking energy recovery measures for specific users,it is necessary to identify the users whose driving habits account for a large proportion of braking energy,and select the braking energy recovery scheme through cost and benefit conversion.In this paper,the calculation model of brake energy recovery intensity is proposed firstly,then typical user examples are extracted through big data platform,then common brake energy optimization measures and their cost estimates are listed,and finally the selection scheme of each exemplary user is selected according to the principle that the benefit is greater than the cost.Customized design based on big data for specific users will be an important direction of future automobile design.
作者
龚春忠
李鹏
单承标
张李侠
GONG Chunzhong;LI Peng;SHAN Chengbiao;ZHANG Lixia
出处
《汽车工程师》
2021年第4期26-29,共4页
Automotive Engineer
基金
浙江省科技计划项目(2018C01056)。
关键词
电动汽车
大数据技术
制动能量回收
定制化设计
Electric vehicle
Big data technology
Brake energy recovery
Customized design
