Greenhouse gas emissions associated with electric vehicle charging: The impact of electricity generation mix in a developing country

Since 2012, the government has been promoting the electric vehicles and the development of related infrastructure to encourage local automakers to explore into the alternatively powered vehicles. However, the benefits of grid-dependent EVs can only be harvested under the condition that their use is coupled with a low carbon electricity grid. Thus, it is an additional challenge for Malaysia's that are largely dependent on fossil fuels for electricity generation. The object of this paper is to perform a well-to-wheel life cycle assessment for calculating the greenhouse gas emissions attributable to the usage of ICEVs, HEVs and EVs in Malaysian scenario. These emission calculations will provide the best information for policymakers, researchers, and investors to make appropriate and effective decisions on policies, research and investments in future transport energy. The results show that running EVs with national grid will produce an average of 7% more GHG emissions than HEVs at the same distance. However, they will produce an average of 19% less GHG emissions than the ICEVs. Overall the GHG emissions produced through the usage of EVs are substantial based on the well-to-wheel analysis, as the environmental profile of EVs is linked with the national grid. Therefore, in order to harvest the benefit of EVs towards climate change and global warming mitigation, massive modernization and transformation should be taken for the development of the national grid towards greener sources.     

Hybrid- and battery-electric vehicles offer low-cost climate benefits in China

Car ownership in China is expected to grow dramatically in the coming decades. If growing personal vehicle demand is met with conventional cars, the increase in greenhouse gas emissions will be substantial. One way to mitigate carbon dioxide (CO₂) emissions from passenger travel is to meet growing demand for cars with alternative vehicles such as hybrid- and battery-electric vehicles (HEVs and BEVs). Our study examines the cost-effectiveness of transitioning from conventional cars to HEVs and BEVs, by calculating their marginal abatement cost (MAC) of carbon in the long-run. We find that transitioning from conventional to hybrid and battery electric light-duty, four-wheel vehicles can achieve carbon emissions reductions at a negative cost (i.e. at a net benefit) in China. In 2030, the average MAC is estimated to be about −$140/ton CO₂ for HEVs and −$515/ton CO₂-saved for BEVs, varying by key parameters. The total mitigation potential of each vehicle technology is estimated to be 1.38 million tons for HEVs and 0.75 million tons for BEVs.     

纯电动乘用车驱动电机选配

文章旨在通过分析纯电动乘用车与传统内燃机汽车在动力系统方面的差别，在以经验公式进行计算的基础上，根据前者动力系统的特点，结合某一款纯电动乘用车的项目，初步提出了纯电动汽车动力系统匹配的基本要求；通过分析现有驱动电机的特点，基于动力性、经济性、续航能力及噪声等因素的考虑，找到了一种能满足现阶段电动车开发的电机种类和参数的选配标准。     

信号电气设备空气断路器的种类和选用

城轨交通信号系统的各设备负载都由电源屏和UPS统一供电,而能达到各负载分路供电的电气元件则是通过空气断路器完成.在信号系统的维护过程中,空气断路器选择不当,可能带来很多麻烦.因此,从断路器的种类、功能、应用等几方面,详细介绍了断路器选用时的注意事项.     

基于四轮轮边驱动电动车的路面附着系数估算方法

路面附着系数是影响车辆行驶安全性的重要因素,利用轮边驱动电动汽车驱动力矩可以对路面利用附着系数进行观测。当观测到μ-λ曲线接近于峰值点时,将该时刻的轮胎利用附着系数作为路面峰值附着系数,并根据识别的路面峰值附着系数进行驱动防滑控制。该方法能够有效防止轮胎滑转,提高车辆行驶稳定性。     

轮边驱动系统对车辆垂向性能影响的研究现状

由于引入轮毂电机,使得轮边驱动电动汽车驱动系统的质量显著增加,引起整车非簧载质量相对过大,恶化了车辆垂向性能。在查阅国内外大量文献的基础上,详细介绍了对轮边驱动系统相关问题的研究现状,具体分析了非簧载质量过大对车辆垂向性能的影响以及国内外解决该问题的主要方法和效果,最后对轮边驱动系统未来发展趋势进行了展望。     

基于C167CS微控制器的混合动力整车主控制器研制

混合动力汽车(HybridElectricVehicle,HEV)具备了内燃机汽车加油方便、续驶里程长和纯电动汽车污染少、效率高的优点,已经成为汽车界竞相开发的热点。本文结合混合动力汽车开发的项目实践,阐述了基于英飞凌C167CS微处理器的整车主控制器的硬件、底层驱动软件、安全模式的设计思路以及各节点间CAN通讯的硬件实现。详细介绍了英飞凌产品:16位控制器C167CS、CAN总线收发器TLE6250G、继电器驱动用上位开关BTS724的具体应用。     

XL纯电动轿车CAN总线系统及应用层协议的开发

为了满足XL纯电动轿车控制实时性和可靠性要求，提出了基于CAN总线的分布式控制系统拓扑结构，开发的CAN总线应用层协议，包括通信内容、ID编码、数据编码、数据格式、消息调度以及底层接口定义等6部分。文中还介绍了所开发的基于CAN总线的硬件在环测试系统。通过硬件在环测试、台架联合调试和道路试验对CAN总线系统进行综合实测和评价。实际运行表明，纯电动汽车CAN总线系统具有较高的可靠性和实时性。     

Development of driving cycles for electric vehicles in the context of the city of Florence

Strong efforts are spent in automotive engineering for the creation of so called Driving Cycles (DCs). Vehicle DC development has been a topic under research over the last thirty years, since it is a key activity both from an authority and from an industrial research point of view. Considering the innovative characteristics of Electric Vehicles (EVs) and their diffusion on certain contexts (e.g. city centers), the demand for tailored cycles arises. A proposal for driving data analysis and synthesis has been developed through the review and the selection of known literature experiences, having as a goal the application on a EVs focused case study. The measurement campaign has been conducted in the city of Florence, which includes limited traffic areas accessible to EVs. A fleet of EVs has been monitored through a non-invasive data logging system. After data acquisition, time-speed data series have been processed for filtering and grouping. The main product of the activity is a set of DCs obtained by pseudo-randomized selection of original data. The similarity of synthetic DCs to acquired data has been verified through the validation of cycle parameters. Finally, the new DCs and a selection of existing ones are compared on the basis of relevant kinematic parameters and expected energy consumption. The method followed for the creation of DCs has been implemented in a software package. It can be used to generate cycles and, under certain boundary conditions, to get a filtered access to the measured data and provide integration within simulation environment.     

Optimum routing of battery electric vehicles: Insights using empirical data and microsimulation

This study investigates the energy consumption impact of route selection on battery electric vehicles (BEVs) using empirical second-by-second Global Positioning System (GPS) commute data and traffic micro-simulation data. Drivers typically choose routes that reduce travel time and therefore travel cost. However, BEVs’ limited driving range makes energy efficient route selection of particular concern to BEV drivers. In addition, BEVs’ regenerative braking systems allow for the recovery of energy while braking, which is affected by route choices. State-of-the-art BEV energy consumption models consider a simplified constant regenerative braking energy efficiency or average speed dependent regenerative braking factors. To overcome these limitations, this study adopted a microscopic BEV energy consumption model, which captures the effect of transient behavior on BEV energy consumption and recovery while braking in a congested network. The study found that BEVs and conventional internal combustion engine vehicles (ICEVs) had different fuel/energy-optimized traffic assignments, suggesting that different routings be recommended for electric vehicles. For the specific case study, simulation results indicate that a faster route could actually increase BEV energy consumption, and that significant energy savings were observed when BEVs utilized a longer travel time route because energy is regenerated. Finally, the study found that regenerated energy was greatly affected by facility types and congestion levels and also BEVs’ energy efficiency could be significantly influenced by regenerated energy.