Identifying the optimal control strategy is a challenging task requiring for multiple strategies to be tried, 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.
Fast-Response Model Surrogates
In general terms, in order to simulate control applications some simplification of the model physics are made. This can often result in loss of model robustness, as such cmcl innovations have developed a number of key fast-response model surrogate models and methodologies suitable for application to key engine processes. These can be employed to map the response of detailed physics-based models.
This enables for the inherent detail and predictive capabilities of our modelling technologies such as SRM Engine Suite to be employed in developing more robust advanced control strategies. One example of this is expressed in more detail in the described user story.
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.