ISC provides independent, high quality control engineering consultancy and R & D services to the automotive industry, typically in powertrain control.
ISC specialises in:
Optimal control solutions can range from simple classical feedback/feedforward to advanced control, such as model-based methods like MPC. In all cases, simplicity remains a key objective in our solutions, providing performance criteria can be met.
Our standard control design software tools include MATLAB/Simulink and LabVIEW, including the range of dedicated Powertrain Controls Software and Hardware Modules from National Instruments. Our services can be tailored to specific applications or company needs and help clients shorten their learning curve.
Our clients include automotive manufacturers, Tier-1 suppliers and ECU suppliers such as General Motors, Toyota, Chrysler, Ford, Cummins, Jaguar, Ricardo, Visteon and Freescale.
Over the years, ISC has delivered many training courses to Ford, Cummins, Chrysler, Toyota and Jaguar, ranging from introductory level courses for groups who need an awareness of control applied to engines to advanced control topics for research teams.
We have powertrain control specific materials, including hands-on with simulations of engines where different methods of engine control can be studied to support our lectures.
We can adapt individual courses to suit your company's needs.
This is a rolling programme of research undertaken for a major automotive company, to investigate the modelling, estimation and model based control techniques to enhance engine control systems while meeting the increasingly tight emission regulations. Methods explored include MPC (linear and nonlinear), hierarchical strategies and hybrid control of mixed variable problems (e.g. changing number of cylinders in use).
Several of the developed schemes have been tested on real engine drive cycles.
Diesel engine control involves complex nonlinear dynamics. These result in non-minimum phase behaviour and steady-state gain-sign reversals, which vary with the engine operating conditions. ISC tackled these control challenges using advanced multivariable state-dependent optimal control. The main control objectives were to supply the requested engine torque, while minimising fuel consumption and reducing NOx and particulate matter emissions. Three key actuators were available to achieve the objectives: the fuel injector, the Exhaust Gas Recirculation (EGR) valve, and the Variable Geometry Turbine or Turbocharger (VGT).
Model-based predictive control (MPC) was used for Spark Injection (SI) engines to handle constraints and compensate for actuator, process and sensor delays. Nonlinear models were required to represent the nonlinearities and event-based dynamics inherent to automotive engine systems. Linear Parameter-Varying (LPV) models were found to meet the requirements and were used within the Nonlinear MPC framework to control torque tracking, fuel economy, emissions and drivability. Model-based design procedures were used to validate the algorithms in simulation and to optimise them for real-time implementation, prior to the successful tests on the engine itself.