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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.

In recent years, HCCI (Homogeneous Charge Compression Ignition) combustion concept has attracted attention due to its potential for high fuel efficiency and low emissions. The essence of HCCI combustion is auto ignition of a very lean, homogeneous air-fuel mixture. However it leads to a major challenge for control engineers – controlling combustion timing to achieve required torque and optimal fuel consumption. There is a need for a simplified HCCI engine model to guide control strategy development. This paper presents such a control oriented model for a “heated intake air” HCCI engine concept that uses two streams of air (cold and hot) to achieve a variable temperature at intake valve closing.

Modern gasoline engines have increased part-load fuel economy and specific power output through technologies such as downsizing, turbocharging, direct injection, and exhaust gas recirculation. These engines tend to have higher sensitivity to driving behavior because of the steady-state efficiency versus output characteristics (e.g., sweet spot at lower output) and the dynamic response characteristics (e.g., turbo lag). It has been observed that the technologies aimed at increased engine efficiency may improve fuel economy for less aggressive cycles and drivers while hurting fuel economy for more aggressive cycles and drivers. The higher degrees of freedom in these engines and the increased sensitivity make controls and calibration more complex and more important at the same time.

This paper presents a Short Time Fourier Transform based algorithm to identify unknown parameters in fuel dynamics system during engine cold start and warm-up. A first order system is used to model the fuel dynamics in a port fuel injection engine. The feed forward transient fuel compensation controller is designed based on the identified model. Experiments are designed and implemented to verify the proposed algorithm. Different experiment settings are compared.

A number of variables in a conventional automotive powertrain are scheduled on-line based on the current operating conditions with the goal to achieve the best fuel economy (FE), emissions, and performance. The functions are obtained off-line, i.e. after a mapping, data regression, and optimization process followed by in-vehicle calibration for fine-tuning the powertrain behavior. More complex engines, referred to as high degree of freedom (HDOF) engines, require a careful tradeoff between the mapping, optimization, and calibration time on one hand and the achieved accuracy on the other. Additionally, the powertrain control module (PCM) has limited computational resources. Thus, fully representing the more complex functions can be prohibitive. As a result, an HDOF powertrain in actual operation may not completely achieve the potential benefits the new technologies offer.