Intelligent Diagnostics and Prognostics of Electric Vehicle Powertrains

电动汽车(EV)技术将很快给交通行业带来革命性的变化。电动汽车的性能主要取决于其动力总成的功能，特别是电池组和驱动感应电机(IM)。电机的不完善会导致电动汽车发生故障，降低电动汽车的动力效率和行驶安全性。另一方面，锂离子技术还处于早期阶段。无论电池有多好，它都会随着时间的推移而在每次充放电循环中退化。由于挥发性、易燃性和熵变化，电池可能会因过热而着火。电池故障不仅会造成不便和维修费用，还可能带来灾难性的后果，特别是在乘用车上。因此，这项研究计划的长期目标是开发新的技术和工具，以提高电动汽车动力总成智能诊断和预测(IDP)的可靠性。IDP系统可用于实时监控驱动电机的健康状况。它还可以有效地估计电池的寿命状态，提高电池的性能、效率和寿命，优化车辆运行。未来五年，具体研究主题包括：(1)将开发新的混合技术，以提高IMS中轴承故障检测的可靠性；(2)将开发智能分类器，用于实时监测电动汽车驱动电机的健康状况；(3)将提出新的诊断系统，以检查电池的健康状态；(4)将开发混合智能预测器，以预测电池的剩余使用寿命。将提出适当的机器学习算法，以提高相关智能系统的决策收敛和稳健性。这一多学科的研究计划将为在相关学术领域培训HQP提供独特和前沿的机会。由于IMS和电池也普遍用于其他工业和家庭应用，开发的IDP技术和工具不仅可以显著造福加拿大的电动汽车和混合动力汽车工业部门，还可以帮助使用IMS和电池的广泛工业和家庭应用，促进经济增长，保护环境，提高加拿大公司在全球市场的竞争力。

Electric vehicle (EV) technology will soon revolutionize the transportation industry. EV performance depends mainly on the functionality of its powertrain, especially the battery pack and the drive induction motor (IM). The imperfections in the motor will generate EV malfunction, and degrade its power efficiency and drive safety. On the other hand, Lithium ion technology is still in its early stages. No matter how good a battery is, it will degrade over time with every charge/discharge cycle. Due to volatility, flammability and entropy changes, a battery could ignite by overheating. Battery failure will not only result in inconvenience and repair costs, but also risk catastrophic consequences especially in passenger vehicles. Accordingly, the long term objective of this research program is to develop new technology and tools to improve the reliability of intelligent diagnosis and prognosis (IDP) in EV powertrains. The IDP system can be used to monitor the health condition of the drive motors in real-time. It can also effectively estimate battery state of life, improve battery performance, efficiency and lifespan, and optimize vehicle operation. Over the next five years, the specific research themes include: (1) new hybrid techniques will be developed to improve the reliability of bearing fault detection in IMs; (2) An intelligent classifier will be developed for real-time health condition monitoring of drive motors in EVs; (3) A new diagnostic system will be proposed to examine battery state of health; and (4) a hybrid intelligent predictor will be developed to predict the remaining useful life of batteries. Appropriate machine learning algorithms will be proposed to improve the decision-making convergence and robustness of the related intelligent systems. This multidisciplinary research program will provide unique and leading-edge opportunities to train HQP in the related academic fields. Since IMs and batteries are also commonly used in other industrial and domestic applications, the developed IDP technology and tools can not only significantly benefit the EV and hybrid EV industrial sectors in Canada, but can also help with a wide range of industrial and domestic applications using IMs and batteries, boosting the economy, protecting the environment, and enhancing the competitiveness of Canadian companies in the global market.