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This paper describes a ‘toolbox’ for modeling liquid cooling system networks within vehicle thermal management systems. Components which can be represented include pumps, coolant lines, control valves, heat sources and heat sinks, liquid-to-air and liquid-to-refrigerant heat exchangers, and expansion tanks. Network definition is accomplished through a graphical user interface, allowing system architecture to be easily modified. The elements of the toolbox are physically based, so that the models can be applied before hardware is procured. The component library was coded directly into MATLAB / SIMULINK and is intended for control system development, hardware-in-the-loop (HIL) simulation, and as a system emulator for on-board diagnostics and controls purposes. For HIL simulation and on-board diagnostics and controls, it is imperative that the model run in real-time.

Despite the fact that urea-based selective catalytic reduction (SCR) of NOx is a key technology for achieving on- and off-highway diesel emission standards, significant control challenges remain. Transient operation, combined with dramatic changes in catalyst dynamics over the operating range, cause highly nonlinear system behavior. Moreover, these effects depend on catalyst formulation and new catalysts continue to be developed. With many controllers, any difference in catalyst formulation, converter size, and engine emissions calibration require control system re-tuning. To minimize control development effort, this paper presents a novel “generic” controller for SCR systems. Control action is grounded in a physics-based, nonlinear, embedded model. Through the model, controller parameters are adjusted a priori for catalyst formulation and converter size. The few remaining tuning levers are quite intuitive, and require no special knowledge of controls theory.

Selective catalytic reduction (SCR) of NOx is coming into worldwide use for automotive diesel emissions control. To meet the most stringent standards, NOx conversion efficiency must exceed 80% while NH3 emissions or slip must be kept below 10-30 ppm. At such high levels of performance, non-uniformities in ammonia-to-NOx ratio (ANR) at the converter inlet can limit the achievable NOx reduction. Despite its significance, this effect is frequently ignored in 1D catalyst models. The corresponding model error is important to system integration engineers because it affects system sizing, and to control engineers because it affects both steady-state and dynamic SCR converter performance. A probability distribution function (PDF) based method is introduced to include mixture non-uniformity in a 1D, real-time catalyst model.