Next Electric Drives for Future Electric Cars

未来电动汽车的下一代电力驱动

• 批准号: RGPIN-2020-05997
• 负责人: Kar, Narayan
• 金额: $ 4.01万
• 依托单位: University of Windsor
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=718146
• 关键词: Next; Electric; Drives; Future; Cars

The largest obstacle to the mass adoption of electric vehicles (EVs) is the creation of affordable, attractive and functional EV designs for industry and consumers. Eliminating this obstacle involves the design and development of innovative traction electric machines (emachines) and drives that are cost effective, highly efficient, and provide improved torque density and performance. The applicant has made significant progress in achieving enhanced emachines and drives for EV applications. Innovations made in the emachine area include: 1) improvement of core materials and winding coating and insulation, 2) geometrical design and optimization, 3) emachine control and performance analysis, and 4) thermal modeling. In the area of motor drives, progress made includes new inverter topology, reduced losses and reduced total harmonic distortion, and optimized control algorithms. The applicant is currently investigating wide band gap device based motor drives through ongoing research projects. These advancements have resulted in superior electric drive performance and increased EV driving range. Significant improvement was also achieved in the testing of emachines and drives through the development of faster and accurate new testing methods, and the creation of a user friendly data analysis interface with high capability. Several innovative initiatives, both ongoing and planned for the future, will be supported by this proposal which will further build upon the success already achieved by the applicant in the field of emachines and controls. These initiatives include: In collaboration with his partners the applicant will continue to investigate the utilization of lightweight and emerging materials for magnetic and nonmagnetic emachine parts for enhanced electrical and mechanical properties and improved thermal performance. Utilizing multifunctional, multiconstraint based iterative optimization techniques and stochastic evolutionary methods, geometrical optimization will be conducted that will result in an easily manufactured multipurpose emachine with improved performance while reducing material consumption and cost. The proposed program will continue to improve the emachine control performance in terms of responsiveness, torque ripple reduction, and fault tolerance by employing novel parameter independent adaptive control algorithms. The proposed enhanced multipurpose model reference adaptive control algorithm will result in improved charging operation with balanced currents and increased efficiency. The developed multipurpose emachines will be tested and verified in terms of electromagnetic, thermal, and structural performance along with the proposed control methods.

大规模采用电动汽车的最大障碍是为工业和消费者创造负担得起的，有吸引力的和功能性的电动汽车设计。要消除这一障碍，就需要设计和开发创新的牵引电机（电机）和驱动器，这些电机和驱动器具有成本效益、高效率，并提供更高的扭矩密度和性能。申请人在实现电动汽车应用的增强型电机和驱动器方面取得了重大进展。在电机领域的创新包括：1）改进磁芯材料和绕组涂层和绝缘，2）几何设计和优化，3）电机控制和性能分析，以及4）热建模。在电动机驱动领域，取得的进展包括新的逆变器拓扑结构，减少损耗和减少总谐波失真，以及优化控制算法。申请人目前正在通过正在进行的研究项目研究基于宽带隙器件的电机驱动器。这些进步带来了上级电力驱动性能和增加的EV续驶里程。通过开发更快、更准确的新测试方法，以及创建用户友好的高性能数据分析界面，在机器和驱动器的测试方面也取得了显着改进。 本提案将支持几项正在进行和计划进行的创新举措，这些举措将进一步巩固申请人在电子机械和控制领域已经取得的成功。这些举措包括： 申请人将与其合作伙伴合作，继续研究将轻质和新兴材料用于磁性和永磁机器部件，以增强电气和机械性能并改善热性能。 利用多功能、多约束的迭代优化技术和随机进化方法，将进行几何优化，这将导致易于制造的多用途机器，具有改进的性能，同时降低材料消耗和成本。 所提出的方案将继续提高电机控制性能的响应，转矩涟漪减少，并采用新的参数独立的自适应控制算法的容错性。所提出的增强型多用途模型参考自适应控制算法将导致改进的充电操作与平衡电流和提高效率。 所开发的多用途电机将在电磁、热和结构性能沿着以及所提出的控制方法方面进行测试和验证。