Article
Thermodynamics
Xiangyang Xu, Jiangling Zhao, Junwei Zhao, Kai Shi, Peng Dong, Shuhan Wang, Yanfang Liu, Wei Guo, Xuewu Liu
Summary: This study provides a thorough comparison between the series hybrid transmission (SHT) and series-parallel hybrid transmission (SPHT) for different types of vehicles and driving cycles. The results show that SPHT has notable advantages in fuel saving compared with SHT, especially in high-speed driving cycles for type C vehicles, while there is a negligible difference in fuel consumption between the two for type A vehicles under urban driving cycles. The SPHT has a fuel saving of approximately 7.2% more than the SHT for type B vehicles under the Worldwide Harmonized Light Vehicles Test Cycle (WLTC).
ENERGY CONVERSION AND MANAGEMENT
(2022)
Article
Engineering, Mechanical
Donghai Hu, Jiongzhi Zhang, Leli Hu, Jianwei Li, Qingqing Yang
Summary: Variable driving conditions can lead to switching between multiple drive modes in an integrated starter generator hybrid powertrain, where the addition of a permanent magnet synchronous motor complicates the electromechanical coupling characteristics. By establishing a nonlinear model and predicting the instability boundary during mode switches, the study aims to address the challenges posed by unstable behavior and speed fluctuations in drive systems.
NONLINEAR DYNAMICS
(2021)
Article
Energy & Fuels
Jingzheng Fan, Bingfeng Zu, Jianwei Zhou, Zhen Wang, Haopeng Wang
Summary: An adaptive mode selection strategy based on variable power reserve is proposed in this paper to allow the vehicle to switch modes effectively considering the battery power limitation. The strategy proves to be effective in simulation, reducing total driving power drop by 74.2% under high-speed US06 cycle and 65% under city FTP cycle while maintaining stable fuel consumption and battery utilization rate.
Article
Energy & Fuels
Guangyuan Qiao, Ping Zheng, Mingqiao Wang, Faliang Liu, Yong Liu
Summary: This study investigates a hybrid-magnet variable-flux machine with a variable series-parallel magnetic circuit. By adjusting the magnetization state, the machine achieves improved efficiency and torque capability in high-speed operation.
Article
Thermodynamics
Wenjun Pan, Yitao Wu, Yao Tong, Jie Li, Yonggang Liu
Summary: This paper proposes an energy management strategy optimized by dynamic programming for a series-parallel hybrid electric vehicle. The strategy is modeled and validated with experimental data, and the mapping relationship between control variables and driving conditions is analyzed. The influence of the engine warm-up process on fuel consumption is investigated, and the optimal operating mode distribution of clutches and the optimal power of the engine and motor are extracted to generate the real-time strategy.
ENERGY CONVERSION AND MANAGEMENT
(2023)
Article
Engineering, Electrical & Electronic
Jiankun Peng, Hailong Zhang, Chunye Ma, Hongwen He
Summary: This article investigates the impact of powertrain parameters on the fuel economy of a plug-in hybrid electric bus (PHEB) and proposes a global optimal strategy based on the dynamic programming algorithm for energy management. A combinatorial optimization algorithm, combining a multi-island genetic algorithm (MIGA) and non-linear programming by quadratic Lagrangian (NLPQL), is designed for global and local optimization. Hardware-in-the-loop (HIL) experiments validate the effectiveness of the strategy, with the fuel consumption per 100 km reduced from 25.7-l to 22.9-l diesel and the electricity consumption per 100 km reduced from 14.7 to 14.3 kW.h.
IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Jin Woo Bae, Kwang-Ki K. Kim
Summary: An energy-efficient supervisory control method for parallel hybrid electric vehicles is proposed to improve fuel economy and reduce emissions, utilizing dynamic programming and Gaussian process regression to optimize power management. The method achieved significant fuel efficiency improvements in real-world driving conditions, showcasing the potential for practical application in the automotive industry.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Thermodynamics
Jiayi Hu, Jianqiu Li, Zunyan Hu, Liangfei Xu, Minggao Ouyang
Summary: This study introduces a novel dual-engine system with the incorporation of dynamic programming algorithm for energy management, achieving lower fuel consumption compared to conventional hybrid systems.
Article
Thermodynamics
Lanqi Zhou, Dongpo Yang, Xiaohua Zeng, Xuanming Zhang, Dafeng Song
Summary: This paper proposes a multi-objective real-time energy management system based on model predictive control (MPC) to tackle the increasing complexity of energy management strategy (EMS) control. A short-term speed prediction model based on whale optimization algorithm is developed to balance accuracy and efficiency. An adaptive SOC trajectory planning method is established to plan MPC reference trajectory. Furthermore, a multi-objective real-time MPC (MOR-MPC) algorithm is proposed to optimize fuel efficiency, electrical energy consumption, and battery aging in real-time. Simulation and hardware-in-the-loop (HIL) testing validate the effectiveness and real-time performance of the proposed strategy, achieving a cost reduction of 6.15% and improved real-time performance.
ENERGY CONVERSION AND MANAGEMENT
(2023)
Article
Thermodynamics
Dhrupad Biswas, Susenjit Ghosh, Somnath Sengupta, Siddhartha Mukhopadhyay
Summary: This study proposes a fast iterative implementation of Model Predictive Static Programming (MPSP) algorithm for energy management of Parallel Hybrid Electric Vehicles (PHEVs). The performance of this algorithm is evaluated and compared with other standard methods, with promising results. The MPSP algorithm shows close performance to the ideal performance achieved with Dynamic Programming (DP) and outperforms Linear Time-Varying MPC (LTV-MPC) and Sequential Quadratic Programming MPC (SQP-MPC) in terms of execution time, making it a strong candidate for on-board vehicle implementation of an optimal energy management strategy for PHEVs.
Article
Engineering, Electrical & Electronic
Guangyuan Qiao, Mingqiao Wang, Faliang Liu, Yong Liu, Ping Zheng
Summary: A novel hybrid-PM variable-flux PMSM with series-parallel magnetic circuits is proposed in this article, which shows great potential in the electric vehicle industry. Through analysis of its electromagnetic performance, inductance characteristics, and torque capacity, it is evident that this machine has significant advantages in operational efficiency and performance.
IEEE TRANSACTIONS ON MAGNETICS
(2021)
Article
Engineering, Electrical & Electronic
Bruno Colonetti, Erlon Finardi, Samuel Brito, Victor Zavala
Summary: Unit commitment is a complex problem in power system operations that has yet to be fully solved. Operators currently use optimization solvers and simplifications to address the problem, but solving it in a timely manner remains a challenge. This study proposes a parallel dynamic integer programming approach for solving the unit commitment problem, which has been successfully applied to different power systems with impressive speed-ups compared to sequential strategies.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Chemistry, Multidisciplinary
Bernardo Tormos, Benjamin Pla, Pau Bares, Douglas Pinto
Summary: Due to air quality concerns and rising fuel prices, urban bus fleets are increasingly adopting hybrid electric vehicles (HEVs) for their higher efficiency and lower emissions. This paper proposes an algorithm to adapt the energy management strategy (EMS) of HEVs to specific driving conditions on a particular bus route. The algorithm estimates the driving cycle based on a previous trip and applies dynamic programming and one-step look-ahead to optimize energy consumption. Simulation results show that the proposed method can keep the battery charge within the required range and achieve near-optimal performance.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Civil
Zhen Shen, Can Luo, Xisong Dong, Wanze Lu, Yisheng Lv, Gang Xiong, Fei-Yue Wang
Summary: In this paper, a two-level control strategy combining Adaptive-Equivalent Consumption Minimization Strategy (A-ECMS) and Adaptive Dynamic Programming (ADP) is proposed for controlling Hybrid Electric Vehicles (HEVs). This strategy saves energy and increases the stability of the State of Charge (SOC).
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Computer Science, Interdisciplinary Applications
Mohsen Dastpak, Fausto Errico, Ola Jabali
Summary: This article studies a stochastic variant of the vehicle routing problem (VRP) in the context of domestic donor collection services. They propose a Markov Decision Process (MDP) formulation and a Q-learning algorithm called QN-CO to solve the problem. Their computational analysis shows that QN-CO outperforms benchmark policies and can compete with specialized methods for known customer locations and expected demands in advance.
COMPUTERS & OPERATIONS RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
C. Mayet, J. Welles, A. Bouscayrol, T. Hofman, B. Lemaire-Semail
MATHEMATICS AND COMPUTERS IN SIMULATION
(2019)
Article
Engineering, Electrical & Electronic
Bao-Huy Nguyen, Ronan German, Joao Pedro F. Trovao, Alain Bouscayrol
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2019)
Article
Engineering, Electrical & Electronic
Kaibo Li, Shouliang Han, Shumei Cui, Alain Bouscayrol
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2019)
Article
Energy & Fuels
Adnane Houbbadi, Rochdi Trigui, Serge Pelissier, Eduardo Redondo-Iglesias, Tanguy Bouton
Article
Engineering, Electrical & Electronic
Anatole Desreveaux, Alain Bouscayrol, Rochdi Trigui, Elodie Castex, John Klein
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2019)
Article
Engineering, Electrical & Electronic
Ronan German, Seima Shili, Anatole Desreveaux, Ali Sari, Pascal Venet, Alain Bouscayrol
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2020)
Article
Energy & Fuels
Anatole Desreveaux, Alain Bouscayrol, Elodie Castex, Rochdi Trigui, Eric Hittinger, Gabriel-Mihai Sirbu
Article
Energy & Fuels
Bao-Huy Nguyen, Joao Pedro F. Trovao, Ronan German, Alain Bouscayrol
Article
Chemistry, Multidisciplinary
Ali Castaings, Walter Lhomme, Rochdi Trigui, Alain Bouscayrol
APPLIED SCIENCES-BASEL
(2020)
Article
Computer Science, Information Systems
Anatole Desreveaux, Eric Hittinger, Alain Bouscayrol, Elodie Castex, Gabriel Mihai Sirbu
Proceedings Paper
Engineering, Electrical & Electronic
Abdoulaye Pam, Alain Bouscayrol, Philippe Fiani, Fabien Faval
2019 IEEE VEHICLE POWER AND PROPULSION CONFERENCE (VPPC)
(2019)
Proceedings Paper
Energy & Fuels
David Ramsey, Tony Letrouve, Alain Bouscayrol, Phillipe Delarue
2019 21ST EUROPEAN CONFERENCE ON POWER ELECTRONICS AND APPLICATIONS (EPE '19 ECCE EUROPE)
(2019)
Proceedings Paper
Automation & Control Systems
A. Pam, A. Bouscayrol, P. Fiani, F. Faval, P. Barrade
Proceedings Paper
Automation & Control Systems
Zetao Ma, Alain Bouscayrol, Walter Lhomme, Shumei Cui
