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The interactions between automatic controls, physics, and driver is an important step towards highly automated driving. This study investigates the dynamical interactions between human-selected driving modes, vehicle controller and physical plant parameters, to determine how to optimally adapt powertrain control to different human-like driving requirements. A cyber-physical system (CPS) based framework is proposed for co-design optimization of the physical plant parameters and controller variables for an electric powertrain, in view of vehicle’s dynamic performance, ride comfort, and energy efficiency under different driving modes. System structure, performance requirements and constraints, optimization goals and methodology are investigated. Intelligent powertrain control algorithms are synthesized for three driving modes, namely sport, eco, and normal modes, with appropriate protocol selections. The performance exploration methodology is presented.

This paper presents a coordinated controller for comprehensive optimization of vehicle dynamics performance and energy consumption for a full drive-by-wire electric vehicle, which is driven by a four in-wheel motor actuated (FIWMA) system and steered by a steer-by-wire (SBW) system. In order to coordinate the FIWMA and SBW systems, the mechanisms influencing the vehicle dynamics control performance and the energy consumption of the two systems are first derived. Second, the controllers for each subsystem are developed. For the SBW system, a triple-step control technique is implemented to decouple the yaw rate and sideslip angle controls. The FIWMA system controller is designed with a hierarchical control scheme, which is able not only to satisfy the yaw rate and sideslip angle tracking demands, but also to deal with actuation redundancy and constraints.