The resulting MPC controller was evaluated against a baseline, state of the art PI-controller and a solution based on dynamic programming that represents the theoretical maximum in fuel efficiency because it solves the problem over the whole driving cycle. The latter solution cannot be implemented in real-time due to its significant computational requirements. The algorithms generated with FORCES Pro, on the other hand, could be deployed to the CONVENIENT prototype truck to evaluate the system in tests.
For two representative drive cycles, the MPC controllers implemented with FORCES Pro achieved a reduction in the power consumption of the alternator of 16% and 18% over the baseline controller, respectively. The theoretically maximal reduction computed with dynamic programming for the two cycles were 34% and 19%, respectively, indicating that FORCES Pro can realize a major portion of the possible fuel savings. Operational constraints are of course satisfied since they are included in the FORCES Pro design from the beginning.
Despite the more sophisticated control methodology used, development time of MPC controllers with FORCES Pro is significantly reduced for two main reasons: On the one hand, the systematic, model-based approach to control design does not necessitate extensive test-drives and cumbersome hand-tuning of control parameters by experts. On the other hand, the auto code generation capabilities of FORCES Pro let the control engineers focus on the control problem rather than implementation and algorithmic issues, shortening prototyping cycles and reducing the number of implementation errors that have to be fixed.
Details about the CONVENIENT research project can be found at http://www.convenient-project.eu/ while the control problem considered here and related work is described in the following publications:
Lindgärde, O., Feng, L., Tenstam, A., and Söderman, M., "Optimal Vehicle Control for Fuel Efficiency," SAE Int. J. Commer. Veh. 8(2):682-694, 2015, doi:10.4271/2015-01-2875.
Lindgärde, O., Söderman, M., Tenstam, A., and Feng, L., "Optimal Complete Vehicle Control for Fuel Efficiency," Transportation Research Procedia 14: 1087-1096, 2016, doi:10.1016/j.trpro.2016.05.179.
Johannesson, L., Murgovski, N., Jonasson, E., Hellgren, J., Egardt, B., "Predictive energy management of hybrid long-haul trucks", Control Engineering Practice 41: 83-97, August 2015, doi:10.1016/j.conengprac.2015.04.014.