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It is desirable for an engine control system to maintain a stable combustion. A high combustion variability (typically measured by the relative variations in produced work, COV(IMEP)) can indicate the use of too much EGR or a too lean air-fuel mixture, which results in less engine efficiency (in terms of fuel and emissions) and reduced driveability. The coefficient of variation (COV) of the ion current integral has previously been shown in several papers to be correlated to the coefficient of variation of IMEP for various disturbances (e.g. AFR, EGR and fuel timing). This paper presents a cycle-to-cycle ion current based method of estimating the approximate category of IMEP (either normal burn, slow burn, partial burn or misfire) for the case of lean air-fuel ratio. The rate of appearance of the partial burn and misfire categories is then shown to be well correlated with the onset of high combustion variability (high COV(IMEP)).

This paper investigates the use of the ionization current to estimate the Coefficient of Variation for the Indicated Mean Effective Pressure, COV(IMEP), which is a common variable for combustion stability in a spark ignited engine. Stable combustion in this definition implies that the variance of the produced work, measured over a number of consecutive combustion cycles, is small compared to the mean of the produced work. The COV(IMEP) is varied experimentally either by increasing EGR flow or by changing the air-fuel ratio, in both a laboratory setting (engine in dynamometer) and in an on-road setting. The experiments show a positive correlation between COV(Ion integral), the Coefficient of Variation for the integrated Ion Current, and COV(IMEP), when measured under low load on an engine in a dynamometer, but not under high load conditions. On-road experiments show a positive correlation, but only in the EGR and the lean burn case.

A method for robust tuning of individual cylinders air-fuel ratio is proposed. The fuel injection is adjusted so that each cylinder has the same air-fuel ratio in inner control loops, and the resulting air-fuel ratio in the exhaust pipe is controlled with an exhaust gas oxygen sensor (EGO) in an outer control loop to achieve stoichiometric air-fuel ratio. Correction factors to provide cylinder individual fuel injection timing are calculated based on measurements of the ion currents for the individual cylinders. An implementation in a production vehicle is shown with results from driving on the highway.

Estimation of combustion variability can be performed by using ion currents measured at the spark plug. A scheme is here proposed that exploits the potential of using measurements from multiple cylinders to improve the estimation accuracy of combustion variability (measured by the coefficient of variation of IMEP). This is realised by dividing combustion variability into categories and having one classifier running for each cylinder with the ion current as input signal. The final estimate of combustion variability is then formed by a majority vote among the classifiers. This scheme is shown to improve estimation accuracy by up to 15% on measurements taken from highway driving in a production vehicle.

This paper compares several strategies for air-fuel ratio transient control. The strategies are: A factory standard look-up table based system (a SAAB Trionic 5), a feedback PI controller with and without feed-forward throttle correction, a linear feed-forward control algorithm, and two nonlinear feed-forward algorithms based on artificial neural networks. The control strategies have been implemented and evaluated in a SAAB 9000 car during a transient driving test, consisting of an acceleration in the second gear from an engine speed of 1500 rpm to 3000 rpm. The best strategies are found to be the neural network based ones, followed by the table based factory system. The two feedback PI controllers offer the poorest performance.