Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 1: data requirements, processing, and analysis

Abstract

This is the first part of a study investigating a model-based transient calibration process for diesel engines. The motivation is to populate hundreds of parameters (which can be calibrated) in a methodical and optimum manner by using model-based optimization in conjunction with the manual process so that, relative to the manual process used by itself, a significant improvement in transient emissions and fuel consumption and a sizable reduction in calibration time and test cell requirements is achieved. Empirical transient modelling and optimization has been addressed in the second part of this work, while the required data for model training and generalization are the focus of the current work. Transient and steady-state data from a turbocharged multicylinder diesel engine have been examined from a model training perspective. A single-cylinder engine with external air-handling has been used to expand the steady-state data to encompass transient parameter space. Based on comparative model performance and differences in the non-parametric space, primarily driven by a high engine difference between exhaust and intake manifold pressures (DP) during transients, it has been recommended that transient emission models should be trained with transient training data. It has been shown that electronic control module (ECM) estimates of transient charge flow and the exhaust gas recirculation (EGR) fraction cannot be accurate at the high engine DP frequently encountered during transient operation, and that such estimates do not account for cylinder-to-cylinder variation. The effects of high engine DP must therefore be incorporated empirically by using transient data generated from a spectrum of transient calibrations. Specific recommendations on how to choose such calibrations, how many data to acquire, and how to specify transient segments for data acquisition have been made. Methods to process transient data to account for transport delays and sensor lags have been developed. The processed data have then been visualized using statistical means to understand transient emission formation. Two modes of transient opacity formation have been observed and described. The first mode is driven by high engine DP and low fresh air flowrates, while the second mode is driven by high engine DP and high EGR flowrates. The EGR fraction is inaccurately estimated at both modes, while EGR distribution has been shown to be present but unaccounted for by the ECM. The two modes and associated phenomena are essential to understanding why transient emission models are calibration dependent and furthermore how to choose training data that will result in good model generalization.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 2: modelling and optimization

“…A BoxCox [15] transform was used for the emission models based on previous work by Brahma et al [16,17], which suggests that an exponential dependence of emissions on engine parameters increases prediction accuracy because it represents the physical phenomena better than a linear quadratic expression. However, the Box-Cox transform, commonly used by statisticians, imposes an exponential dependence between emissions and all independent variables, as illustrated by equation (1). This cannot parallel the physical phenomena; for example, it is hard to imagine an exponential relationship between PM and engine speed (r/min) or injection timing, but not for the oxygen mole fraction ln(Y ) = a 0 + a 1 engine speed + a 2 timing + a 3 O 2 fraction.…”

“…These cycles were chosen from the 31 FTP cycles and corresponding snap throttle cycles described in the companion work [1] to span the calibration spectrum in an equidistant manner. No FTP cycle data were included in the training data to ensure that the model was not 'memorizing' the FTP cycle.…”

“…The current work asks three questions not found in the literature. 1. What kind of empirical modelling methods are most suitable for modelling transient emissions and torque?…”

A decision-tree-based approach to smoke spike detection in a heavy-duty diesel engine

“…[1][2][3] It was noticed that many kinds of empirical model could 'fit' the PM data but model predictions for test data generated from any transient calibration which are significantly different from that used to generate the training data were poor, i.e. models were calibration dependent.…”

Investigation of Combustion Phasing Control Strategy During Reactivity Controlled Compression Ignition (RCCI) Multicylinder Engine Load Transitions

“…This controller was able to prevent excessive ignition delay and to improve NOx/HC emissions. Brahma and Chi [26] also developed a model-based transient cali bration process by using both steady-state and transient data. The NOx and PM rates measured for initial and final federal test proce dure (FTP) runs were significantly improved by using their pro posed transient calibration method.…”