The development of the next generation of integrated chassis controllers for high performance passenger cars.

该博士项目由迈凯轮汽车公司共同出资，由国际领先的监督团队参与，将专注于开发用于高性能乘用车的下一代集成底盘控制器。这些控制器将通过主动悬架控制和其他驱动系统来提高乘坐舒适性和车辆动力学。博士课程的第一年将为项目发展奠定基础。这包括创建和实验验证由车辆模型、相关执行系统模型、状态估计器、工业赞助商提供的一套基准控制器和相关后处理工具组成的模型在环开发环境。在第一年内，还将适当注意对文献的分析和确认报告的准备(大学要求)。第二年和第三年的博士活动将集中于新型集成底盘控制器的制定、实施和模拟，以及它们在真实车辆原型上的实验评估。底盘控制器将基于以下组合：a)计算效率高的非线性模型预测控制技术；b)智能控制/人工智能，根据车辆当前的运行状况在线更新控制器参数；以及c)通过车辆连接实现创新的先发制人控制技术，使用有关预期道路情景(例如道路曲率曲线)的信息来增强控制系统性能。将针对现有的基准控制器对新型控制器的潜力进行批判性分析。特别是，第二年的工作将针对非线性模型预测控制器的基于公式和仿真的实施活动，包括先发制人方面，而最后一年将专门用于人工智能方面和算法的实验评估。博士论文的撰写将在项目的最后6个月进行。这一博士项目的研究预计将产生高质量的期刊出版物(至少三份四分之一的期刊出版物)，并在特定学科领域产生长期的学术和产业影响。

Co-funded by McLaren Automotive and involving an internationally leading supervisory team, this PhD project will focus on the development of the next generation of integrated chassis controllers for high performance passenger cars. The controllers will enhance ride comfort and vehicle dynamics through active suspension control and other actuation systems. The first year of the PhD programme will set the foundations for the project developments. This includes the creation and experimental validation of a model-in-the-loop development environment consisting of a vehicle model, relevant actuation system models, state estimators, a set of benchmarking controllers provided by the industrial sponsor, and relevant post processing tools. Within the first year, appropriate attention will also be paid to the analysis of the literature, and the preparation of the confirmation report (University requirement). The second and third years of the PhD activity will focus on the formulation, implementation and simulation of the novel integrated chassis controllers as well as their experimental assessment on real vehicle prototypes. The chassis controllers will be based on the combination of: a) computationally efficient nonlinear model predictive control technology; b) intelligent control / artificial intelligence for the online update of the controller parameters depending on the current operating conditions of the vehicle; and c) innovative pre-emptive control techniques enabled by vehicle connectivity, using the information on the expected road scenario ahead (e.g., road curvature profile) to enhance control system performance. The potential of the novel controllers will be critically analysed with respect to the available benchmarking controllers. In particular, the effort of the second year will target the formulation and simulation based implementation activities of the nonlinear model predictive controllers including the pre-emptive aspects, while the final year will be dedicated to the artificial intelligence aspects and the experimental assessment of the algorithms. The write-up of the PhD thesis will be carried out in the final 6 months of the project. The research of this PhD project is expected to generate high-quality journal publications (at least three quartile 1 journal publications), and to have long-term academic and industrial impact in the specific subject area.