Ignoring the driver’s torque command can be beneficial for fuel economy, especially if it leads to extended residence time at efficient operating conditions. We answered this question for a particular engine, which allows mode switches between spark ignition (SI) and homogeneous charge compression ignition (HCCI) combustion. When operating such a multimode combustion engine it might be required to defer a load command outside the feasible regime of one combustion mode until a mode switch is accomplished. The resulting delays in engine torque response might negatively affect vehicle performance and drivability. In this paper a longitudinal vehicle model is presented, which incorporates dynamics associated with SI/HCCI mode switching. Two exemplary supervisory control strategies were evaluated in terms of fuel economy and torque behavior. It was seen that the duration of a mode switch may be short enough to avoid substantial impairment in torque response. This in turn would lead to the opportunity of purposefully ignoring the driver command. Thereby, the residence time in the beneficial HCCI combustion regime is prolonged and fuel-expensive mode switching avoided. The result is a trade-off between torque deviation and improvements in fuel economy. Finally, based on this trade-off the supervisory control strategy relying on a short-term prediction of engine load was seen to achieve similar fuel economy with slightly improved torque response than a strategy without prediction.
- Dynamic Systems and Control Division
Is it Economical to Ignore the Driver? A Case Study on Multimode Combustion
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Nüesch, SP, & Stefanopoulou, AG. "Is it Economical to Ignore the Driver? A Case Study on Multimode Combustion." Proceedings of the ASME 2015 Dynamic Systems and Control Conference. Volume 1: Adaptive and Intelligent Systems Control; Advances in Control Design Methods; Advances in Non-Linear and Optimal Control; Advances in Robotics; Advances in Wind Energy Systems; Aerospace Applications; Aerospace Power Optimization; Assistive Robotics; Automotive 2: Hybrid Electric Vehicles; Automotive 3: Internal Combustion Engines; Automotive Engine Control; Battery Management; Bio Engineering Applications; Biomed and Neural Systems; Connected Vehicles; Control of Robotic Systems. Columbus, Ohio, USA. October 28–30, 2015. V001T11A003. ASME. https://doi.org/10.1115/DSCC2015-9875
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