Publications

• Journal Paper
  • Zhu, Zhaoxuan, Nicola Pivaro, Shobhit Gupta, Abhishek Gupta, and Marcello Canova “Safe Model-based Off-policy Reinforcement Learning for Eco-driving in Connected and Automated Hybrid Electric Vehicles.” arXiv preprint arXiv:2105.11640 (2021). (submitted to IEEE Transactions on Intelligent Vehicles)
  • Zhu, Zhaoxuan, Shobhit Gupta, Abhishek Gupta, and Marcello Canova. “A Deep Reinforcement Learning Framework for Eco-driving in Connected and Automated Hybrid Electric Vehicles.” arXiv preprint arXiv:2101.05372 (2021). (submitted to IEEE Transactions on Intelligent Transportation Systems)
  • Zhu, Zhaoxuan, Shawn Midlam-Mohler, and Marcello Canova. “Development of physics-based three-way catalytic converter model for real-time distributed temperature prediction using proper orthogonal decomposition and collocation.” International Journal of Engine Research 22, no. 3 (2021): 873-889.
• Conference Paper
  • Zhu, Zhaoxuan, Shobhit Gupta, Nicola Pivaro, Shreshta Rajakumar Deshpande, and Marcello Canova. “A GPU Implementation of a Look-Ahead Optimal Controller for Eco-Driving Based on Dynamic Programming.” arXiv preprint arXiv:2104.01284 (2021). (accepted by 2021 European Control Conference)
  • Zhu, Zhaoxuan, Yuxing Liu, and Marcello Canova. “Energy Management of Hybrid Electric Vehicles via Deep Q-Networks.” In 2020 American Control Conference (ACC), pp. 3077-3082. IEEE, 2020.
  • Zhu, Zhaoxuan, Marcello Canova, and Shawn Midlam-Mohler. “A physics-based three-way catalytic converter model for real-time prediction of temperature distribution.” IFAC-PapersOnLine 51, no. 31 (2018): 166-171.