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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.

Current methods of storing critical engine operating parameters often rely on lookup interpolation functions. A drawback to lookup interpolations is that as the number of independent variables increases, the function's dimensions increase from tables to cubes to hypercubes of data. A sparser collection of data may serve if the strict orthogonal structure of lookup functions is not required. Instead of forming a matrix of data for every combination of input variables, a few critical data points are stored with their independent variables. The available data can be used to estimate parameters at new input values (typically from current measurements) by relating the available data by its distance from the new inputs. An inverse distance weighting scheme is used to calculate the output of the function.

Advancing intake valve timing shortly after engine crank and run-up can potentially reduce vehicle cold start hydrocarbon (HC) emissions in port fuel injected (PFI) engines equipped with intake variable cam timing (iVCT). Due to the cold metal temperatures, there can be significant accumulation of liquid fuel in the intake system and in the cylinder. This accumulation of liquid fuel provides potential sources for unburned hydrocarbons (HCs). Since the entire vehicle exhaust system is cold, the catalyst will not mitigate the release of unburned HCs. By advancing the intake valve timing and increasing valve overlap, liquid fuel vaporization in the intake system is enhanced thereby increasing the amount of burnable fuel in the cylinder. This increase in burnable HCs must be countered by a reduction in injector-delivered fuel via a compensator that reacts to cam movement.

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.