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Control of vehicle powertrain thermal management systems is becoming more challenging as the number of components is growing, and as a result, advanced control methods are being investigated. Model predictive control (MPC) is particularly interesting in this application because it provides a suitable framework to manage actuator and temperature constraints, and can potentially leverage preview information if available in the future. In previous SAE publications (2015-01-0336 and 2016-01-0215), a robust MPC control formulation was proposed, and both simulation and powertrain thermal lab test results were provided. In this work, we discuss the controller deployment in a vehicle; where controller validation is done through road driving and on a wind tunnel chassis dynamometer. This paper discusses challenges of linear MPC implementation related to nonlinearities in this over-actuated thermal system.

Low-Pressure Exhaust Gas Recirculation (LP-EGR) has been shown to be an effective means of improving fuel economy and suppressing knock in downsized, boosted, spark ignition engines. LP-EGR is particularly beneficial at low-speed, high-load conditions, but can lead to combustion instability at lower loads. The transport delays inherent in LP-EGR systems slow the reduction of intake manifold EGR concentrations during tip-out events, which may lead to excessive EGR concentrations at low load. This paper explores leveraging Variable Valve Timing (VVT) as a means of improving the rate of reduction of intake manifold EGR concentration prior to tip-out. At higher boost levels, high valve overlap may result in intake manifold gas passing directly to the exhaust manifold. This short-circuiting behaviour could potentially improve EGR evacuation rates.

An advanced powertrain cooling system with appropriate control strategy and active actuators allows greater flexibility in managing engine temperatures and operating near constraints. An organized controls development process is necessary to allow comparison of multiple configurations to select the best way forward. In this work, we formulate, calibrate and validate a Model Predictive Controller (MPC) for temperature regulation and constraint handling in an advanced cooling system. A model-based development process was followed; where the system model was used to develop and calibrate a gain scheduled linear MPC. The implementation of MPC for continuous systems and the modification related to implementing switching systems has been described. Multiple hardware configurations were compared with their corresponding control system in simulations. The system level requirements were translated into MPC calibration parameters for consistent comparison between multiple configurations.

Numerous studies describe the fuel consumption benefits of changing the powertrain temperature based on vehicle operating conditions. Actuators such as electric water pumps and active thermostats now provide more flexibility to change powertrain operating temperature than traditional mechanical-only systems did. Various control strategies have been proposed for powertrain temperature set-point regulation. A characteristic of powertrain thermal management systems is that the operating conditions (speed, load etc) change continuously to meet the driver demand and in most cases, the optimal conditions lie on the edge of the constraint envelope. Control strategies for set-point regulation which rely purely on feedback for disturbance rejection, without knowledge of future disturbances, might not provide the full fuel consumption benefits due to the slow thermal inertia of the system.