Influence of an Automatic Transmission with a Model Predictive Control and an On-Demand Clutch Actuator on Vehicle Fuel Consumption 2016-01-1115
The demand for lower CO2 emissions requires not just the optimization of every single component but the complete system. For a transmission system, it is important to optimize the transmission hardware as we well as the interaction of powertrain components. For automatic transmission with wide ratio spreads, the main losses are caused by the actuation system, which can be reduced with use of ondemand actuation systems. In this paper, a new on-demand electromechanical actuation system with validation results on a clutch test bench is presented. The electro-mechanical actuator shows an increase in the efficiency of 4.1 % compared to the conventional hydraulic actuation in a simulated NEDC (New European Driving Cycle) cycle. This increase is based on the powerless end positions of the actuator (engaged and disengaged clutch). The thermal tension and wear are compensated with a disk spring. This allows a stable control over service life. This actuation system is developed for a new 7-speed automatic transmission layout and with a model predictive controller the fuel economy and comfort issues are optimized. The decrease in fuel consumption is achieved with an optimized shift strategy depending on the driver type determination. This enables 13 % lower fuel consumption for a small gasoline passenger car (vehicle mass: 1250 kg, air drag coefficient: 0.3, roll resident coefficient: 0.01, total powertrain efficiency NEDC: 20 %) in the NEDC simulation compared to manual shifting defined by legislation. The combination of an on-demand electro-mechanical actuator and a model predictive transmission controller is shown to achieve a fuel consumption reduction of 17.1 % for a small gasoline passenger car.
Citation: Huth, T. and Pischinger, S., "Influence of an Automatic Transmission with a Model Predictive Control and an On-Demand Clutch Actuator on Vehicle Fuel Consumption," SAE Technical Paper 2016-01-1115, 2016, https://doi.org/10.4271/2016-01-1115. Download Citation