In this webinar we will demonstrate how to automatically tune the shift schedule for an automotive transmission using optimization algorithms. Using a dynamic model of a dual-clutch transmission that uses measured data to estimate fuel economy, optimization algorithms are used to tune the transmission shift schedule to maximize fuel economy.
This webinar will include demonstrations and explanations to show you how to:
- Create a vehicle model that is useful for control design, optimization studies, and HIL
- Import measurement data to estimate fuel economy
- Tune abstracted models to match simulation results from detailed models
- Use parallel computing to accelerate parameter sweeps and optimization studies
- Find the global minimum for complex optimization problems
Tight vehicle emission regulations and high fuel prices have intensified the demand for fuel-efficient cars. Tuning the transmission shift schedule is an important part of improving fuel economy, but since the shift schedule has many parameters, manual tuning of these values is a tedious option that will only find the optimal values by luck. Solving the problem using simulation, optimization algorithms, and parallel computing can ensure that a truly optimal shift schedule is found.
View the example code used in this webinar here:
Dual Clutch Transmission example code
About the Presenter: Steve Miller is responsible for the technical marketing of the physical modeling tools at MathWorks. Steve joined MathWorks as an Application Engineer in 2005 and moved to the Design Automation Marketing group in 2006. Prior to that, Steve worked at Delphi Automotive in Braking Control Systems and at MSC.Software as an Adams specialist, consulting in various capacities at Ford, GM, Hyundai, BMW, and Audi. Steve has a B.S. in Mechanical Engineering from Cornell University and an M.S. in Mechanical Engineering from Stanford University
