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Mathematical models of a torque sensor equipped crankshaft in a light-duty diesel engine are identified, validated, and compared. The models are based on in-cylinder pressure and crankshaft torque data collected from a 5-cylinder common-rail diesel engine running at multiple operating points. The work is motivated by the need of a crankshaft model in a closed-loop combustion control system based on crankshaft torque measurements. In such a system a crankshaft model is used in order to separate the measured crankshaft torque into cylinder individual torque contributions. A method for this is described and used for IMEP estimation. Not surprisingly, the results indicate that higher order models are able to estimate crankshaft torque more accurately than lower order models, even if the differences are small. For IMEP estimation using the cylinder separation method however, these differences have large effects on accuracy.

Different Vibe function model structures for parameterized diesel engine heat release models are investigated. The work is motivated by the need of such models when closed-loop combustion control is implemented based on torque domain combustion phasing analysis. Starting from the studied model structures, models are created by estimating the model parameters using a separable least squares approach. After this, the models are evaluated according to two different performance criteria. The first criterion rates the ability of the estimated models to describe reference mass fraction burned traces. The second criterion assesses how accurately the models estimate the reference combustion phasing measure. As expected, the analysis shows that the models based on the most flexible model structure achieve the best results, both regarding mass fraction burned estimation and combustion phasing estimation.

A simulation model for the dynamic properties of multi-cylinder engines is developed. Specifically, the model is used to describe the relation between the individual cylinder pressures and the resulting torque in the crankshaft. The model is validated against a 5-cylinder SI-engine equipped with a crankshaft integrated torque sensor. The simulation model developed is based on a system of first order nonlinear differential equations where the crankshaft dynamics are expressed as interconnected mass-spring-damper elements. The motivation is to investigate how instantaneous crankshaft torque measurements can be used to deduce information on the combustion process, cylinder by cylinder, for the purpose of engine control. Therefore, a computationally simple simulation method is introduced.

A two-state forward dynamic programming algorithm is evaluated in a series hybrid drive-train application with the objective to minimize fuel consumption when look-ahead information is available. The states in the new method are battery state-of-charge and engine speed. The new method is compared to one-state dynamic programming optimization methods where the requested generator power is found such that the fuel consumption is minimized and engine speed is given by the optimum power-speed efficiency line. The other method compared is to run the engine at a given operating point where the system efficiency is highest, finding the combination of engine run requests over the drive-cycle that minimizes the fuel consumption. The work has included the engine torque and generator power as control signals and is evaluated in a full vehicle-simulation model based on the Volvo Car Corporation VSIM tool.

The development and implementation of a new structure for data-driven models for NOX and soot emissions is described. The model structure is a linear regression model, where physically relevant input signals are used as regressors, and all the regression parameters are defined as grid-maps in the engine speed/injected fuel domain. The method of using grid-maps in the engine speed/injected fuel domain for all the regression parameters enables the models to be valid for changes in physical parameters that affect the emissions, without having to include these parameters as input signals to the models. This is possible for parameters that are dependent only on the engine speed and the amount of injected fuel. This means that models can handle changes for different parameters in the complete working range of the engine, without having to include all signals that actually effect the emissions into the models.

The three-way-catalyst (TWC) is an essential part of the exhaust aftertreatment system in spark-ignited powertrains, converting nearly all toxic emissions to harmless gasses. The TWC’s conversion efficiency is significantly temperature-dependent, and cold-starts can be the dominating source of emissions for vehicles with frequent start/stops (e.g. hybrid vehicles). In this paper we develop a thermal TWC model and calibrate it with experimental data. Due to the few number of state variables the model is well suited for fast offline simulation as well as subsequent on-line control, for instance using non-linear state-feedback or explicit MPC. Using the model could allow an on-line controller to more optimally adjust the engine ignition timing, the power in an electric catalyst pre-heater, and/or the power split ratio in a hybrid vehicle when the catalyst is not completely hot.