Learning Slip Control of an Engine Clutch in a Parallel Hybrid Electric Vehicle for Linear Vehicle Launch 2014-01-1745
This work studied the control technique for the engine clutch engagement at launch for the TMED parallel HEV for the improved drivability and dynamic performance. Analysis are done on the speed synchronization of the clutch plates, the speed control using the starter motor (ISG), and the fluid pressure control for the clutch. Possible external factors such as changes in the friction coefficient of transmission fluid, temperature variation, auxiliary power and pressure losses are identified and their effects on the targeted dynamic performance are examined.
The targeted system performance was achieved with a learning control technique using fluid pressure as the only control input. This involves the compensation for the effect of external factors on the fluid pressure profile and this effect is memorized for the subsequent slip-launch application. To simulate the dynamics of the drivetrain including the engine clutch at various driving scenarios, a simulation model including the clutch slip dynamics is built. Using the simulation model, the learning factors for the fluid pressure are obtained and its sensitivity on the targeted drivability is analyzed under various driving conditions. By breaking down the error components on the pressure profile, the control compensation points for each of the external factors are found.
It is found through the simulations that it requires maximum of two learning iterations to bring the error within the allowable bounds. With analysis on the several external factors, the control method achieved the desired performance with minimum number of learning.