Modelling and estimation of combustion variability for fast light-off of diesel aftertreatment
Bryan P. Maldonado, Anna G. Stefanopoulou, Michiel Van Nieuwstadt, Brien Fulton, John Hoard, Mitchell Bieniek
Abstract
Bryan P. Maldonado, Anna G. Stefanopoulou, Michiel Van Nieuwstadt, Brien Fulton, John Hoard, Mitchell Bieniek
Abstract
Combustion phasing retard is commonly used on diesel engines to achieve faster aftertreatment light-off and lower tailpipe emissions. Aggressive combustion phasing retard can achieve higher exhaust gas enthalpy at the cost of increased combustion variability, which can create vehicle noise, vibration, and harshness (NVH) issues. To avoid such issues while maximising exhaust heating, feedback from cylinder pressure sensors can be used to control the coefficient of variation of the indicated mean effective pressure (CoVIMEP) to a maximum allowable value. Therefore, a control-oriented combustion model that captures the stochastic properties of the cycle-to-cycle variability for IMEP has been developed for control design. Unbiased estimation methods for the CoVIMEP using finite impulse response (FIR) and infinite impulse response (IIR) filters are discussed. Finally, the performance of the estimation strategy is tested during an engine warm-up phase to show that it is a suitable alternative for generating a feedback signal for control.
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Combustion phasing retard is commonly used on diesel engines to achieve faster aftertreatment light-off and lower tailpipe emissions. Aggressive combustion phasing retard can achieve higher exhaust gas enthalpy at the cost of increased combustion variability, which can create vehicle noise, vibration, and harshness (NVH) issues. To avoid such issues while maximising exhaust heating, feedback from cylinder pressure sensors can be used to control the coefficient of variation of the indicated mean effective pressure (CoVIMEP) to a maximum allowable value. Therefore, a control-oriented combustion model that captures the stochastic properties of the cycle-to-cycle variability for IMEP has been developed for control design. Unbiased estimation methods for the CoVIMEP using finite impulse response (FIR) and infinite impulse response (IIR) filters are discussed. Finally, the performance of the estimation strategy is tested during an engine warm-up phase to show that it is a suitable alternative for generating a feedback signal for control.
Key concepts: Automotive engineering, Diesel fuel, Combustion, Estimation, Environmental science, Engineering, Chemistry, Systems engineering