Real time performance improvement of engineering control units via Higher Order Singular Value Decomposition: Application to a SI engine

This article presents a method that improves the real time performance of some optimisation algorithms used in engineering control units. The motivation behind the improvement is the fact that when these algorithms are based on a computationally expensive set of model equations, real time optimisation is seldom possible. This is, for example, the case of most of the existing engine control units (ECUs) in the automotive and aeronautic sectors that are based on plain interpolation between multidimensional tables rather than on an artificial intelligence approach. In this article, the model equations are replaced by a reduced model based on Higher Order Singular Value Decomposition, which has the ability to provide simplified global descriptions of multidimensional databases. Such global description is amenable to efficient integration within an intelligent search formulation and sufficiently accurate for engineering applications. To illustrate the method, a Genetic Algorithm (GA) is used to optimise the working parameters of a spark ignition reciprocating engine. The goal is to find out, in a short CPU time (less than one-tenth of a second), the values of some engine control parameters (namely intake pressure, intake pipe length, intake valve closing angle, and spark timing) that yield the requested engine power while requiring a minimum specific fuel consumption, and avoiding knock combustion instability. The GA search platform can be replaced by other optimisation algorithms and the method can also be advantageously applied to other engineering systems described by computationally expensive model equations.