The electrification of cars is driving the development of new complex control strategies, hardware and software. Our focus was a holistic approach to modelling, designing and testing control systems.
A comprehensive study of safety protocols for vehicle control systems
A diagnostic strategy for hybrid and electric vehicle (HEV/EV) control systems
Technical specification, design and build of supervisory controller suitable for use in safety critical applications
A suite of computer simulation models to appraise vehicle and sub-system controllers
A proposal for a generic hybrid control architecture including control algorithms for optimising vehicle performance, energy management and driveability
A basic implementation of the Vehicle Supervisory Controller (VSC) architecture was developed and deployed on Tata Vista EVX and Jaguar XJ demonstrator vehicles
Business Impact – New Products and Processes
Ricardo has designed a new supervisory controller using a 32-bit processor with an integrated safety feature. Low level software and a high level design environment have also been developed to allow integration with the high level control algorithms developed in modelling environments. These products will be a valuable addition to Ricardo’s capabilities.
WMG led the collaborative development of a standardised HEV systems modelling framework based on WARPSTAR 2+ (WARwick Powertrain Simulation Tool for ARchitectures). Project partners developed a library of new powertrain and electric machine models in the DYMOLA environment. This will greatly reduce the time required to develop complex vehicle level models.
Tata Motors European Technical Centre (TMETC) has applied the new architecture to the Tata Vista EVX vehicle; initially for development, but with a view to a production unit. TMETC has also applied a generic control architecture to their current hybrid programmes.
WMG and MIRA have developed the concept of a Hybrid System Safety Monitor. Diagnostic strategies and algorithms were developed through Hardware-in-Loop (HiL) testing with simulation models and then applied and correlated on a running Range Extended Electric Vehicle (REEV). TMETC is looking to apply this learning to future production vehicle programmes.