Practical Application of Model Predictive Zonal Temperature Estimation and Control for Vehicle Cabins

Modern vehicles are commonly sold with air conditioning systems. Especially in climates with traditionally high temperatures, these systems are not just for comfort but highly relevant also to safety. Various hardware setups for cooling and heating have been used to climatize the vehicle cabin. No matter which setup is used though, a cabin temperature controller needs to be implemented. Recent developments see an increase of multizone climate control methods. Even though various approaches have been presented, the task of temperature tracking and disturbance rejection remains challenging. In this article, it is shown using experiments that separating cooling circuit control from cabin temperature control does not affect the performance of the cabin control loop. For cabin temperature control, an approach is presented which allows for simultaneous air outlet temperature and mass flow management based on previous work. This is possible in multiple vehicle zones. The approach is based on a gray-box model of vent system and cabin. A mass flow management system based on real-time steady-state optimization grants simultaneous tracking and disturbance rejection. The weakness of this previous work, namely, the dependence on careful hand-tuning and mass flow independent tuning is overcome by applying an adaptive tuning approach. All results are experimentally validated using an experimental vehicle in real traffic for the two-zone control case. Consistent behavior over a wide range of mass flows and temperatures was reached. This correlates to a consistent thermal experience for passengers. Overshoot was effectively eliminated by applying the adaptive tuning. Concluding, an analysis of the move to practical implementation is shown. In this, a cabin temperature observer is presented that demonstrates the difficulties of implementing accurate three-zone control on a limited set of sensors. Based on the implemented cabin temperature observer, tracking can be achieved on a reduced sensor setup albeit at the cost of worse closed-loop controller performance.