Several automotive control problems require a control approach which can deliver a high performance in the presence of both uncertainties and large time-delays. Prime examples are Idle Speed Control (ISC) and Fuel-Air Ratio (FAR) control, both of which have been addressed with success through the use of adaptation. In ISC, the objective is to regulate the engine speed to a prescribed set-point in the presence of accessory load torque disturbances such as due to air conditioning and power steering. The objective in FAR control is to maintain the in-cylinder FAR at a prescribed set point, determined primarily by the state of the Three-Way Catalyst (TWC), so that the pollutants in the exhaust are removed with the highest efficiency. Adaptive Posicast Controller, an adaptive controller for time delay systems, has been used in these two control problems, and have led to a significant performance improvement.
Emission Control
Recent results using a closed-loop adaptive Proportional-plus-Integral (PI) controller show a NOx conversion efficiency of over 95%, with a maximum NH3-slip of less than 5 ppm. An adaptive PI-controller was simulated on the full chemistry model, and shown to be capable of delivering over 90% of NOx conversion efficiency at a peak Ammonia Slip of less than 2 ppm. Preliminary experimental results from a test vehicle have demonstrated that with little to no tuning, efficiency levels of SCR above 80% can be achieved as adaptation proceeds, when driven in city traffic, with a mean ammonia slip of around 20 ppm.1
Adaptive Shift Control
While driving, vehicle occupants notice when an inconsistent shift occurs. This not only degrades the user experience, but the fuel efficiency of the vehicle as well. In regards to powertrain control systems, inconsistent shifts contribute to a significant amount of “things gone wrong”, as reported in consumer surveys. The biggest challenge for consistent shift control comes from a lack of feedback during the torque transfer phase in the presence of nonlinear and varying clutch dynamic response. As a result of this variability and absence of appropriate feedback, current shift control methods do not use actuator models and depend on shaft speed signals for feedback during the inertia transfer phase of the shift. This leads to a mostly open-loop control with limited disturbance rejection and non-robust performance, in particular, during the torque transfer phase. Adaptation is possible only based on previous shift events, thus allowing the occasional non-smooth shift. The objective is to design an enhanced adaptive control during shift, enabled by measurements of the shaft torque. Understanding of the clutch actuator dynamics and deriving suitable clutch models with adaptive parameters for control are the first set of steps of this effort.
We have developed a model a model of the clutch actuation dynamics in a 6-speed automatic transmission similar to the experimental characteristics in the figure above (see solid line). The important dynamics we are considering are approximately between 3 and 4 seconds, which are highly nonlinear. An adaptive shift control based on this model was shown to result in improved performance with swift changes.2
- Ong, C.Y., Annaswamy, A.M., Kolmanovsky, I.V., Laing, P. and Reed, D., 2010. An adaptive proportional integral control of a urea selective catalytic reduction system based on system identification models. SAE International Journal of Fuels and Lubricants, 3(1), pp.625-642. ↩︎
- Thornton, S., Annaswamy, A., Yanakiev, D., Pietron, G.M., Riedle, B., Filev, D. and Wang, Y., 2014, October. Adaptive shift control for automatic transmissions. In Dynamic Systems and Control Conference (Vol. 46193, p. V002T27A001). American Society of Mechanical Engineers. ↩︎