基于联合距离评估法的共享电动汽车驾驶风险评估

Driving Risk Assessment of Shared Electric Vehicles Based on CODAS Method

摘要:

基于模糊信息和多属性决策，提出一套共享电动汽车（SEVs）失效模式与影响分析（FMEA）方法，包括采用互评法进行专家筛选与赋权，构建风险评估标准，采用共识理论对专家意见进行检验，采用贴近度最优化法对风险因子进行客观赋权，引入联合距离评估（CODAS）法对失效模式的风险水平进行排序等。结果表明，高风险的失效模式主要分布在动力系统和行车系统。灵敏度分析和对比分析验证了结果稳健性和方法有效性。最后，提出了可行性安全管理措施建议。

Abstract:

Based on the fuzzy information and multi-attribute decision making， a failure mode and effect analysis （FMEA） method for shared electric vehicles（SEVs） was proposed， including determining experts candidate and their authority weights through mutual evaluation， constructing risk assessment criteria through qualitative analysis， testing expert opinions using consensus theory， objectively weighting risk factors using close degree optimization method， and ranking the risks of failure modes by introducing the combinative distance-based assessment （CODAS） method. The results show that high-risk failure modes are mainly distributed in power system and driving system. The robustness of the results and the validity of the method were verified by sensitivity analysis and comparative analysis. Finally， feasible safety management measures were proposed.