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Thesis Defense: Utilizing a Soft ECU Model to Aid the Development of a Powertrain Control Strategy

Andrew Spiegel, MS Candidate, Mechanical Engineering
Wednesday, April 15, 2015, 9:00 am
2nd Floor Center for Automotive Research
930 Kinnear Road
Columbus, OH 43212


  • Dr. Shawn Midlam-Mohler, Chair (ME)
  • Dr. Marcello Canova (ME)


Automotive control systems are becoming increasingly complex as consumers and government regulations demand vehicles with better fuel economy, reduced emissions, improved safety, and increased functionality while maintaining performance. The short development time frames of embedded control software in automotive electronic control units (ECUs) has put additional attention on methods for rapid control development. Model-based control design is the industry standard for the development of embedded control systems for attributes such as reducing development times, lowering cost, and preventing revisions while ensuring quality of complex control systems [1]. The Ohio State University’s Center for Automotive Research (CAR) is working on a research project for Fiat Chrysler Automobiles to develop a novel powertrain control strategy using model-based design techniques. The powertrain control strategy’s main purpose is to optimize vehicle powertrains for fuel economy, drivability, and performance. To develop the powertrain control strategy, the Ohio State University (OSU) needed a simplified version of Fiat Chrysler’s state-of-the-art powertrain control strategy. Because OSU is under time constraints to develop and demonstrate the control strategy, a soft ECU model representing Fiat Chrysler’s powertrain control strategy was developed. The soft ECU model will help speed the development process of the powertrain control strategy by serving as a benchmark and starting point for control design. This thesis describes the development, verification, and utilization of a soft ECU model. The soft ECU model was developed in Simulink using model-based control techniques. A soft engine ECU model concept was developed with algorithms from Fiat Chrysler’s engine control strategy and validated through co-simulation with a GT-POWER engine model. After several modifications and new calibrations, the soft engine ECU model was verified in open-loop with the real control strategy of a 2011 Chrysler Town and Country minivan at CAR. A soft transmission ECU model was developed using a gear shift algorithm from a previous research project and an artificial neural network (ANN) trained to mimic the torque converter clutch lock-up strategy. The soft transmission ECU model was also verified in open-loop with data from the real vehicle. The soft engine ECU model, soft transmission ECU model, a driver model, and a vehicle plant model were all combined in closed-loop to create a complete vehicle model. The complete vehicle model was verified through model-in-the-loop simulations. The accuracy of the individual models in the complete vehicle model were compared with their respective open-loop accuracies. The complete vehicle model shows good accuracy with corresponding data collected from the real Chrysler minivan. The soft ECU model is an accurate benchmark of Fiat Chrysler’s real powertrain control strategy. Further modifications can be made to the soft ECU model and driver model to improve the overall accuracy of the complete vehicle model. The soft ECU model will be used as a starting point for the design of the new powertrain control strategy.