Article
Engineering, Chemical
Wenxiao Han, Xiaohua Chu, Sui Shi, Ling Zhao, Zhen Zhao
Summary: This paper proposes a reinforcement learning-based energy management method for plug-in hybrid electric buses, which combines different algorithms and introduces a dynamic SOC design zone plan method. The experimental results demonstrate that this method performs well in energy management and fuel consumption.
Article
Green & Sustainable Science & Technology
Daizheng Hou, Yafu Zhou, Qichao Dong
Summary: This paper presents a novel co-design method for plug-in hybrid electric buses (PHEBs) that takes into account both component matching and energy management for multiple bus routes in the city. The proposed method includes an adaptive energy management strategy based on an A-PMP and a dynamic SOC plan, as well as a Taguchi robust design method for component matching. The results show that the proposed method improves fuel economy compared to rule-based control, making it a viable option for co-designing PHEBs for multiple bus routes in the city.
INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING-GREEN TECHNOLOGY
(2023)
Article
Thermodynamics
Yonggang Liu, Bin Huang, Yang Yang, Zhenzhen Lei, Yuanjian Zhang, Zheng Chen
Summary: This paper investigates a hierarchical energy management control strategy for autonomous plug-in hybrid electric vehicles in vehicle-following environment. The strategy includes an upper layer controller with grey neural network and fuzzy adaptive control algorithm, and a lower layer controller with genetic algorithm and fuzzy logic algorithm, to predict speed, plan target speed, and optimize energy consumption, achieving 95.43% optimality compared to dynamic programming results.
Article
Energy & Fuels
Tao Deng, Peng Tang, JunLin Luo
Summary: A novel real-time energy management strategy for PHEVs based on equivalence factor dynamic optimization method is proposed in this paper, which weakens the influence of future driving cycle to the control accuracy and improves computation efficiency.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Engineering, Electrical & Electronic
Ruoyan Han, Renzong Lian, Hongwen He, Xuefeng Han
Summary: This article focuses on the energy management of hybrid electric-tracked vehicles (HETVs) used in agriculture and industry. The influence of steering resistance on energy distribution is considered, and a multi-state energy management strategy (EMS) based on deep deterministic policy gradient (DDPG) is proposed. A multidimensional matrix framework is used to extract parameters of the actor network from a trained DDPG-based EMS. Hardware-in-the-loop (HiL) experiments validate the real-time tractability of the proposed strategy. Results show that the DDPG-based strategy improves fuel economy by 13.1% compared to the double deep Q-learning-based strategy and exhibits adaptability to uncertainty in initial state of charge (SOC).
IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS
(2023)
Article
Thermodynamics
Zhiming Gao, Tim J. LaClair, Kashif Nawaz, Guoyuan Wu, Peng Hao, Kanok Boriboonsomsin, Mike Todd, Matt Barth, Abas Goodarzi
Summary: A comprehensive forward-looking powertrain model with an efficiency-based control strategy was developed for real-time optimization of plug-in hybrid electric buses while considering drivability and practical operation under real driving conditions. Results showed that the innovative powertrain control improved energy savings by 10%-30% compared to the baseline strategy.
ENERGY CONVERSION AND MANAGEMENT
(2022)
Article
Engineering, Electrical & Electronic
Yuxiang Zhang, Rui Ma, Dongdong Zhao, Yigeng Huangfu, Weiguo Liu
Summary: A multi-level energy management strategy is proposed in this article to improve the energy utilization rate of the fuel cell hybrid electric vehicle (FCHEV). The strategy includes the establishment of a system overall efficiency optimization model and the use of an instantaneous optimal search algorithm to design the corresponding load demand power distribution strategy. Experimental results and vehicle driving tests confirm that the proposed energy management strategy can optimize the overall efficiency of the FCHEV hybrid power system, which contributes to the application of FCHEVs.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2023)
Article
Thermodynamics
Feng Wang, Jiaqi Xia, Yingfeng Cai, Jingang Guo
Summary: A novel energy management strategy (EMS-MTC) is proposed in this research to address the issue of frequent mode transitions in plug-in hybrid electric vehicles. By incorporating two penalty functions into the EMS algorithm, a tradeoff between fuel economy and mode transition frequency is achieved. Experimental tests demonstrate the potential practical application of this strategy.
ENERGY CONVERSION AND MANAGEMENT
(2022)
Article
Automation & Control Systems
Chenkun Qi, Dongjin Li, Wei Ma, Qingqing Wei, Wenming Zhang, Wenlong Wang, Yan Hu, Feng Gao
Summary: In this article, a distributed delay compensation approach is proposed for the hybrid simulation system of space manipulator capture, which can compensate for various delays in the system loop, ensuring the stability and simulation accuracy of the system.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)
Article
Engineering, Electrical & Electronic
Yuanjian Zhang, Yanjun Huang, Zheng Chen, Guang Li, Yonggang Liu
Summary: This article presents a novel approach using machine learning-based virtual test controller (VTC) to validate PHEV models, achieving simulations mimicking behaviors of internal combustion engine, motor, and generator. The VTC, developed with least-squares support vector machine, random forest, and ReliefF algorithm, provides a solid framework and convenience for control strategy design.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2022)
Article
Engineering, Electrical & Electronic
Yuanjian Zhang, Zheng Chen, Guang Li, Yonggang Liu, Haibo Chen, Geoff Cunningham, Juliana Early
Summary: This article introduces a virtual test controller based on machine learning that can effectively validate complex vehicle models and improve energy management performance of plug-in hybrid electric vehicles. The validation of the virtual test controller is achieved by utilizing the least-square support vector machine, random forest, and ReliefF algorithm to filter the internal data. The major innovation of this article lies in the development of an efficient virtual test controller, which provides convenience for the development of vehicle models and control strategy design.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2022)
Article
Thermodynamics
Hongxu Zhou, Zhongwei Yu, Xiaohua Wu, Zhanfeng Fan, Xiaofeng Yin, Lingxue Zhou
Summary: This paper develops a dynamic programming-based fuzzy logic strategy for optimizing energy management in a demonstration fuel cell hybrid bus. The strategy considers the relationship between fuel cell power, battery state of charge, and demand power. It is tailored to the unique characteristics of the demonstration driving cycles and shows improved energy efficiency compared to the original rule-based strategy, especially under certain conditions.
Article
Thermodynamics
Dongpo Yang, Tong Liu, Dafeng Song, Xuanming Zhang, Xiaohua Zeng
Summary: This study proposes a Real time Multi-objective optimization Guided-MPC strategy (RMGMPC) for efficiency-oriented power-split hybrid electric buses (PSHEB). The strategy includes a vehicle speed prediction controller, a SOC reference generator, and the novel RMGMPC based on the direct multiple shooting method and sequential quadratic programming algorithm. The proposed RMGMPC achieves high fuel economy, improved shifting times, and reduced calculation time compared to MPC-DP. The results are verified through HIL testing.
Article
Engineering, Mechanical
Wolfgang Witteveen, Lukas Koller, Daniel Penninger
Summary: The iterative algorithm presented in the publication is suitable for coupling numerical and real subsystems, and works for quasi-static and dynamically reacting systems with moderate nonlinearities. This method eliminates the need for controllers, makes data exchange speed less critical, and can only be applied to components whose properties do not change during the simulation.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Engineering, Mechanical
Wolfgang Witteveen, Lukas Koller
Summary: This study extends the existing cyber physical testing methods by decomposing the overall system into experimental and numerical subsystems. The compatibility conditions are considered for updating the input signals, and approximate models can be used to improve convergence in the numerical subsystems.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)