Development of a traction controller for drivability improvement of electric vehicles

这个博士该项目旨在开发防急动和牵引控制器，以改善全电动卡车的驾驶性能。目标车辆将用于城市和城市外的交付，并将面临各种气候和道路条件：从干燥平坦的柏油路面到积雪的上坡路。控制器将在两个不同的演示器上进行测试。第一种是两轮驱动车辆，具有中央电动机、单齿轮变速器、通过半轴和等速万向节连接到车轮的开放式差速器。第二种是在前后轴上都使用以前的传动系统配置的四轮驱动车辆，抗冲击控制器将基于非线性显式模型预测控制技术，并将与文献中的五种不同控制结构进行比较：i）纯前馈控制器; ii）基于电机速度高频分量的反馈控制器; iii）将前馈控制器与反馈干扰观测器组合的系统;以及v）基于估计的传动系扭矩的反馈控制器。在牵引控制器开发中，基准将由基于PID滑差的算法设置，将其与一种新的非线性显式模型预测牵引控制器进行比较。萨里大学汽车工程中心在模型预测控制领域有丰富的经验，因为它是少数几个开发了显式非线性模型预测控制器设计工具箱的研究小组之一。这个工具箱已被利用的牵引力控制器的初步开发的电动车辆与轮内电机，这是一个新奇的文献。尽管如此，这种控制器仍然是概念验证，因为它对于轮胎-道路参数变化不是鲁棒的。这个博士该项目的目标是提高控制器的鲁棒性和技术准备水平，以实现工业可实施的系统。创新控制器的组合及其对工业合作伙伴提供的电动汽车演示器的全面评估将允许在机械和汽车工程领域的四分之一期刊上发表结果。此外，该活动将包括一个广泛的调查，对反挺举控制器，因为文献错过了一个彻底的审查这一主题。

This Ph.D. project aims at developing anti-jerk and traction controllers for the drivability improvement of fully electric lorries. The target vehicles will be employed for urban and extra-urban deliveries, and will face a wide range of climate and road conditions: from dry and flat tarmac to snowy uphill roads. The controllers will be tested on two different demonstrators. The first one is a two-wheel-drive vehicle with a central electric motor, a single gear transmission, an open differential connected to the wheels through half-shafts and constant velocity joints. The second one is a four-wheel-drive vehicle that uses the previous drivetrain configuration on both the front and rear axles.The anti-jerk controller will be based on nonlinear explicit model predictive control technology, and will be compared with five different control structures from the literature: i) a pure feedforward controller; ii) a feedback controller based on the high frequency component of the motor speed; iii) a system combining a feedforward controller with a feedback disturbance observer; iv) a feedback controller based on the drivetrain torsion rate; and v) a feedback controller based on the estimated drivetrain torque.Within the traction controller development, the benchmark will be set by a PID slip based algorithm, which will be compared with a novel nonlinear explicit model predictive traction controller. The Centre for Automotive Engineering of the University of Surrey has experience in the field of model predictive control, as it is one of the few research groups to have developed a toolbox for the design of explicit nonlinear model predictive controllers. This toolbox has been exploited for the preliminary development of a traction controller for an electric vehicle with in-wheels motors, which represents a novelty in the literature. Nevertheless, such controller is still a proof of concept, as it is not robust with respect to tyre-road parameter variations. This Ph.D. project targets the enhancement of the level of robustness and technology readiness of the controller, to achieve an industrially implementable system.The combination of innovative controllers and their comprehensive assessment on the electric vehicle demonstrators provided by the industrial partners will allow the publication of the results in quartile 1 journals in the subject areas of mechanical and automotive engineering. Furthermore, the activity will include an extensive survey on anti-jerk controllers, as the literature misses a thorough review of this topic.