In *30th Electric Vehicle Symposium (EVS30)*, Stuttgart, Germany, October, 2017. ANL

Paper abstract bibtex

Paper abstract bibtex

Increasing connectivity in passenger vehicles provides for a large amount of look-ahead information about driving conditions. An intelligent control algorithm is presented that takes advantage of this information to obtain the operation strategy for the powertrain of a parallel hybrid electric vehicle, in an uncongested highway cruising situation. In order to guarantee sufficient computational efficiency to meet future online requirements, the algorithm is based on Pontryagin’s Minimum Principle. The whole driving/operation strategy is composed of a series of solutions to the optimal control sub-problem for each separate route segment. The control sequence computed offline is then evaluated in Autonomie. The simulation result shows 6% fuel savings compared to a baseline rule-based controller with no speed optimization.

@inproceedings{shen_energy-efficient_2017, address = {Stuttgart, Germany}, title = {Energy-{Efficient} {Cruise} {Control} {Using} {Optimal} {Control} for a {Hybrid} {Electric} {Vehicle}}, url = {https://anl.box.com/s/f6k8to4r6ac1k1dpzy5qrw0yjxww1fe3}, abstract = {Increasing connectivity in passenger vehicles provides for a large amount of look-ahead information about driving conditions. An intelligent control algorithm is presented that takes advantage of this information to obtain the operation strategy for the powertrain of a parallel hybrid electric vehicle, in an uncongested highway cruising situation. In order to guarantee sufficient computational efficiency to meet future online requirements, the algorithm is based on Pontryagin’s Minimum Principle. The whole driving/operation strategy is composed of a series of solutions to the optimal control sub-problem for each separate route segment. The control sequence computed offline is then evaluated in Autonomie. The simulation result shows 6\% fuel savings compared to a baseline rule-based controller with no speed optimization.}, booktitle = {30th {Electric} {Vehicle} {Symposium} ({EVS30})}, author = {Shen, Daliang and Karbowski, Dominik and Jeong, Jongryeol and Kim, Namdoo and Rousseau, Aymeric}, month = oct, year = {2017}, note = {ANL}, keywords = {Autonomie, Connected and Automated Vehicles, DOE SMART, Vehicle control}, }

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