A pure electric vehicle driven by dual motors is taken as the research object and the driving scheme of the driving motor is improved to increase the transmission efficiency of existing electric vehicles.Based on the ...A pure electric vehicle driven by dual motors is taken as the research object and the driving scheme of the driving motor is improved to increase the transmission efficiency of existing electric vehicles.Based on the architecture of the transmission system,we propose vehicle performance parameters and performance indexes of a pure electric vehicle,a time-sharing driving strategy of dual motors.First,the parameters of the battery,motor,and transmission system are matched.Then,the electric vehicle transmission model is built in Amesim and the control strategy is designed in Simulink.With the optimization goal of improving the vehicle’s dynamic performance and driving range,the optimal parameters are determined through analysis.Finally,the characteristics of the motor are tested on the bench.The results show that the energy-saving potential of the timesharing driven double motor is higher,and the driving mileage of the double motor drive is increased by 4%.展开更多
Determining the travel intention of residents with shared electric vehicles(EVs)is significant for promoting the development of low-carbon transportation,considering that common problems such as high idle rate and lac...Determining the travel intention of residents with shared electric vehicles(EVs)is significant for promoting the development of low-carbon transportation,considering that common problems such as high idle rate and lack of attractiveness still exist.To this end,a structural equation model(SEM)based on the theory of multiple motivations is proposed in this paper.First,the influencing motivations for EV sharing are divided into three categories:consumer-driven,program-driven,and enterprise-driven motivations.Then,the intentions of residents in Shanghai to travel with shared EVs are obtained through a survey questionnaire.Finally,an SEM is constructed to analyze quantitatively the impact of different motivations on the travel intention.The results show that consumer-driven motivations with impact weights from 0.14 to 0.63 have the overwhelming impact on travel intention,compared to program-driven motivations with impact weights from−0.14 to 0.15 and enterprise-driven motivations with impact weights from 0.02 to 0.06.In terms of consumer-driven motivations,the weight of green travel awareness is the highest.The implications of these results on the policy to enable large-scale implementation of shared EVs are discussed from the perspectives of the resident,enterprise,and government.展开更多
针对自动共享电动汽车(shared autonomous electric vehicles,SAEV)运行出现的车辆分配不平衡以及充电优化问题,提出了一种基于云-边协调计算的SAEV优化控制策略。首先,给出SAEV再平衡优化模型以及再平衡任务分配算法;其次,考虑使用V2G...针对自动共享电动汽车(shared autonomous electric vehicles,SAEV)运行出现的车辆分配不平衡以及充电优化问题,提出了一种基于云-边协调计算的SAEV优化控制策略。首先,给出SAEV再平衡优化模型以及再平衡任务分配算法;其次,考虑使用V2G和动态电价进行SAEV车队的充放电优化,给出SAEV车队能量交换模型以及出行订单分配算法,以减少整个SAEV车队系统的充电成本;再次,利用云-边协调通信将这些优化结果信息在不同平台间进行互动传输,实现电动汽车的最优充电与迁移策略;最后,通过MATLAB使用真实的深圳出租车数据对该优化控制方法进行验证。结果表明,该框架可降低充电成本,提高交通效率,有望扩展应用到更大规模的系统中。所提云-边协调控制策略将复杂的SAEV优化问题分解成3个子问题进行求解,为SAEV的最优运行提供了一种新的方法。展开更多
基金Supported by Beijing Institute of Technology Research Fund Program for Young Scholars(3030011181911)the National Natural Science Foundation of China(520020025)。
文摘A pure electric vehicle driven by dual motors is taken as the research object and the driving scheme of the driving motor is improved to increase the transmission efficiency of existing electric vehicles.Based on the architecture of the transmission system,we propose vehicle performance parameters and performance indexes of a pure electric vehicle,a time-sharing driving strategy of dual motors.First,the parameters of the battery,motor,and transmission system are matched.Then,the electric vehicle transmission model is built in Amesim and the control strategy is designed in Simulink.With the optimization goal of improving the vehicle’s dynamic performance and driving range,the optimal parameters are determined through analysis.Finally,the characteristics of the motor are tested on the bench.The results show that the energy-saving potential of the timesharing driven double motor is higher,and the driving mileage of the double motor drive is increased by 4%.
基金the National Natural Science Founda-tion of China(Nos.71971139 and 72201172)。
文摘Determining the travel intention of residents with shared electric vehicles(EVs)is significant for promoting the development of low-carbon transportation,considering that common problems such as high idle rate and lack of attractiveness still exist.To this end,a structural equation model(SEM)based on the theory of multiple motivations is proposed in this paper.First,the influencing motivations for EV sharing are divided into three categories:consumer-driven,program-driven,and enterprise-driven motivations.Then,the intentions of residents in Shanghai to travel with shared EVs are obtained through a survey questionnaire.Finally,an SEM is constructed to analyze quantitatively the impact of different motivations on the travel intention.The results show that consumer-driven motivations with impact weights from 0.14 to 0.63 have the overwhelming impact on travel intention,compared to program-driven motivations with impact weights from−0.14 to 0.15 and enterprise-driven motivations with impact weights from 0.02 to 0.06.In terms of consumer-driven motivations,the weight of green travel awareness is the highest.The implications of these results on the policy to enable large-scale implementation of shared EVs are discussed from the perspectives of the resident,enterprise,and government.
文摘针对共享电动汽车通过需求响应参与电力系统备用服务的可调度容量预测问题,基于历史轨迹数据提出一种基于模型无关的元学习(model-agnostic meta-learning,MAML)、卷积神经网络(convolutional neural network,CNN)、长短期记忆网络(long short term memory network,LSTM)和注意力机制(attention mechanism)的可调度容量评估模型,采用LSTM对CNN从历史数据中提取有效的特征向量动态变化进行建模学习,并用MAML对CNN-LSTM网络的初始化参数进行训练,在解决传统神经网络难以有效提取历史序列中潜在高维特征且当时序过长时重要信息易丢失的问题的同时,通过多任务训练对元预测网络进行微调以快速适应新预测任务,从而提高模型的预测精度及泛化能力;加入注意力机制突出对预测结果起关键性作用的时序信息,进一步提高预测精度。仿真结果表明所提模型可以有效预测不同日期类型和不同功能区域共享电动汽车的可调度容量,也为后续共享电动汽车通过需求响应参与电网备用服务的风险评估研究提供参考。
文摘针对自动共享电动汽车(shared autonomous electric vehicles,SAEV)运行出现的车辆分配不平衡以及充电优化问题,提出了一种基于云-边协调计算的SAEV优化控制策略。首先,给出SAEV再平衡优化模型以及再平衡任务分配算法;其次,考虑使用V2G和动态电价进行SAEV车队的充放电优化,给出SAEV车队能量交换模型以及出行订单分配算法,以减少整个SAEV车队系统的充电成本;再次,利用云-边协调通信将这些优化结果信息在不同平台间进行互动传输,实现电动汽车的最优充电与迁移策略;最后,通过MATLAB使用真实的深圳出租车数据对该优化控制方法进行验证。结果表明,该框架可降低充电成本,提高交通效率,有望扩展应用到更大规模的系统中。所提云-边协调控制策略将复杂的SAEV优化问题分解成3个子问题进行求解,为SAEV的最优运行提供了一种新的方法。
