双电机耦合驱动电动汽车驱动模式划分与优化

为充分发挥一款双电机耦合驱动系统电动汽车(DMCP-EV)多驱动模式的节能优势,制定了基于系统效率最优的驱动模式控制策略。根据该双电机耦合驱动系统的结构特点,定义了电机4种驱动模式并分别建立其动力学驱动模型和系统效率模型。在满足动力性要求的前提下,分析并划分了各驱动模式的工作范围,以系统效率为优化目标,采用粒子群优化算法进行优化,获得最佳的驱动模式切换控制和转矩分配策略。开展了Matlab/Simulink仿真和硬件在环试验验证。结果表明,经系统效率优化的驱动模式在满足动力性要求的前提下,有效提高了双电机耦合驱动系统的经济性,能耗降低11%。     

船舶混合动力技术发展趋势分析

通过近年发布的《国际海事组织海运温室气体减排初步战略》等相关减排措施,提出船舶混合动力技术作为优选解决方式。介绍该技术发展背景,阐述其定义、架构及国内外发展应用现状,分析油电混合动力技术、气电混合动力技术的特点,对船舶混合动力技术发展趋势及应用前景进行展望,经调查研究,船舶混合动力推进系统具有操纵性好、效率高及特定工况排放低等特性,减排优势明显。     

纯电动卡车总装混线生产的工艺研究

纯电动卡车的产品特点与传统燃油卡车既有共性又存在差异,对比两种车型的底盘装配和调试工艺后,在传统燃油车总装配线的基础上设计了一套新能源的装配工艺流程,不仅提高总装配车间柔性化生产,还实现了纯电动卡车和燃油卡车的混线生产。     

线性绞车电控系统开发与应用

基于广州打捞局120 000 kN抬浮力打捞工程船配套4 500 kN线性绞车的技术要求,提出线性绞车电控系统设计方案。从线性绞车在打捞工程船中的作业工况、电控系统的通讯架构、线性绞车单台控制及远程联动的自动控制、人机界面操作等方面进行研究,介绍线性绞车电控系统的设计思路,为线性绞车在打捞沉船工作中的正确运用提供了理论支撑和技术保障。     

新能源电力推进对比分析

文章基于全球低碳节能政策,研究并概述了直流微网新能源电力推进系统及其关键技术,对比了以太阳能、蓄电池、氢燃料电池等为主动力的电力推进系统,并分析其性能、综合效率及实际船舶应用,对推进绿色船舶、节能减排等具有重要的实际意义。     

齐齐哈尔市中心城区电动汽车及充电设施需求预测研究

在目前能源危机和环境保护的双重制约下,发展电动汽车已经成为解决能源环境问题的新途径。为适应未来电动汽车快速发展的需要及充电设施的合理规划布局,电动汽车及充电设施的需求预测就显得尤为重要。文中分析了影响齐齐哈尔市电动汽车发展规模的影响因素,结合国内其他省市的经验,考虑齐齐哈尔市实际情况,对齐齐哈尔市中心城区的电动汽车和充电设施发展规模进行了合理预测。     

基于ADVISOR的纯电动汽车动力系统匹配及仿真

纯电动汽车作为新能源汽车行业发展的主要方向,在发展其核心技术中,动力系统的匹配对于发展纯电动汽车具有重要的意义,合理的动力系统匹配影响着汽车的动力性和续航里程等因素。根据纯电动汽车的整车参数和性能指标,计算选择动力系统的基本参数,并利用ADVISOR仿真软件进行仿真分析,为改进技术提供依据,验证了设计的有效性。     

动力锂电池与电力推进船舶发展分析

文章通过对主要类型锂离子电池技术指标和特性进行梳理,研究了锂离子电池的热管理技术、安全性、火灾消防技术等应用重点环节的技术要点,分析了锂电池在船舶动力系统中的作用及全电池动力系统和混合动力系统的技术特点,为应用锂电池的新能源船舶研发提供参考。最后介绍了目前国内外应用储能电池动力船舶的多个典型案例,简要阐述了各个案例中的船舶核心参数和主要特点,总结了当前电池动力船舶的主要应用船型、锂电池类型、应用市场及政策、规范现状,认为锂电池动力船舶的发展前景光明,但在相关政策和船舶规范研究方面尚需进一步完善。     

Consumer preferences for battery electric vehicles: A choice experimental survey in China

To accelerate the diffusion of battery electric vehicles (BEVs), consumer preferences for different products and policy attributes must be determined. Although previous studies have investigated consumer preferences for some product attributes, including purchase price, operation cost, driving range, and charging time, limited studies have discussed the broader aspects of product attributes, such as battery warranty and depreciation rate. Moreover, market-oriented incentives, including the personal carbon trading (PCT) scheme and the tradable driving credits (TDC) scheme, can theoretically be effective alternatives to expensive purchase subsidies. However, there is a lack of empirical evidence that confirms the influence of these two schemes on BEV adoption. To fill these gaps, we conducted a stated preference choice experimental survey in China and investigated the effect of product attributes, existing policy incentives, and two emerging market-oriented incentives on BEV adoption. Our results reveal that along with the main product attributes, battery warranty has a significant positive effect on inducing mainstream consumers to adopt BEVs while no preference difference occurs among existing policy incentives after purchase subsidies are abolished. For young consumers, almost all incentives that reduce the operation cost (e.g., PCT) or increase convenience (e.g., TDC) can increase their adoption of BEVs. These findings can provide important implications for the government with regard to designing novel incentives and promoting BEV adoption.     

Using GPS-data to determine optimum electric vehicle ranges: A Michigan case study

Fuel-switching personal transportation from gasoline to electricity offers many advantages, including lower noise, zero local air pollution, and petroleum-independence. But alleviations of greenhouse gas (GHG) emissions are more nuanced, due to many factors, including the car’s battery range. We use GPS-based trip data to determine use type-specific, GHG-optimized ranges. The dataset comprises 412 cars and 384,869 individual trips in Ann Arbor, Michigan, USA. We use previously developed algorithms to determine driver types, such as using the car to commute or not. Calibrating an existing life cycle GHG model to a forecast, low-carbon grid for Ann Arbor, we find that the optimum range varies not only with the drive train architecture (plugin-hybrid versus battery-only) and charging technology (fast versus slow) but also with the driver type. Across the 108 scenarios we investigated, the range that yields lowest GHG varies from 65 km (55+ year old drivers, ultrafast charging, plugin-hybrid) to 158 km (16–34 year old drivers, overnight charging, battery-only). The optimum GHG reduction that electric cars offer – here conservatively measured versus gasoline-only hybrid cars – is fairly stable, between 29% (16–34 year old drivers, overnight charging, battery-only) and 46% (commuters, ultrafast charging, plugin-hybrid). The electrification of total distances is between 66% and 86%. However, if cars do not have the optimum range, these metrics drop substantially. We conclude that matching the range to drivers’ typical trip distances, charging technology, and drivetrain is a crucial pre-requisite for electric vehicles to achieve their highest potential to reduce GHG emissions in personal transportation.