Review of selection criteria for sensor and actuator configurations suitable for internal combustion engines

This literature review considers the problem of finding a suitable configuration of sensors and actuators for the control of an internal combustion engine. It takes a look at the methods, algorithms, processes, metrics, applications, research groups and patents relevant for this topic. Several formal metric have been proposed, but practical use remains limited. Maximal information criteria are theoretically optimal for selecting sensors, but hard to apply to a system as complex and nonlinear as an engine. Thus, we reviewed methods applied to neighboring fields including nonlinear systems and non-minimal phase systems. Furthermore, the closed loop nature of control means that information is not the only consideration, and speed, stability and robustness have to be considered. The optimal use of sensor information also requires the use of models, observers, state estimators or virtual sensors, and practical acceptance of these remains limited. Simple control metrics such as conditioning number are popular, mostly because they need fewer assumptions than closed-loop metrics, which require a full plant, disturbance and goal model. Overall, no clear consensus can be found on the choice of metrics to define optimal control configurations, with physical measures, linear algebra metrics and modern control metrics all being used. Genetic algorithms and multi-criterial optimisation were identified as the most widely used methods for optimal sensor selection, although addressing the dimensionality and complexity of formulating the problem remains a challenge. This review does present a number of different successful approaches for specific applications domains, some of which may be applicable to diesel engines and other automotive applications. For a thorough treatment, non-linear dynamics and uncertainties need to be considered together, which requires sophisticated (non-Gaussian) stochastic models to establish the value of a control architecture

Observer based controller for internal combustion engine

In this work, an observer-based controller for an internal combustion engine is presented. At first, an algorithm for the estimation of an unknown function of the internal combustion engine is designed, since it is very difficult to obtain direct measurements of this variable. This estimator is based on sliding mode algorithms, providing a finite time and robust estimation, using only measurements from the velocity of the engine. On the other hand, with the measured velocity and the estimates of the other variables, a robust controller is synthesized for the engine. In order to considerate the actuator dynamics, the proposed control scheme is based on the master-slave structure, regarding the controller for the actuator as the slave one. For this scheme, the backstepping algorithm is used to design the master controller. Then, the calculated control input signal to the engine is used as a reference for the throttle actuator which is driven by a direct current (DC) motor. Thus, a high-order sliding mode controller is applied to the actuator in order to track the control input signal and reject perturbations, as the applied mechanical load, regulating the velocity of the combustion engine. Numerical simulations show the efficient performance of this proposal. © 2013 IEEE