Identifying the optimal control strategy is a challenging task requiring for multiple strategies to be tested, disregarded or improved. Through the adoption of computational modelling, a greater number of possible strategies can be examined in shorter timescales than could be achieved from experimental activities alone.


Live controls application in a one-dimensional engine simulation tool

In order to simulate complex control applications, some form of simplification in the physics model is often necessary. This can often result in loss of model robustness, as such CMCL have developed several key fast-response model surrogate models and methodologies that are suitable for application to key engine processes. These can be employed to map the response of detailed physics-based models. This enables the inherent detail and predictive capabilities of our modelling technologies to be employed in developing more robust, advanced control strategies.

Operating strategy can also be optimised using our advanced optimisation tools, these can be employed to adopt a multi-objective cost functions which could for example be minimised for a particular operating point, i.e. fulfilling a specified engine speed and load in a safe way but achieving it at minimum exhaust gas emissions.


Typical Projects

  • Provide maps for the response of the engine for key control input variations
  • Carry out optimisation of transition from SI to HCCI mode and vice versa
  • Gasoline fuel reformation and control of combustion characteristics using hydrogen
  • Identify optimal operating strategy for ideal engine control
  • Optimise injection and spark timing strategy