Article
Thermodynamics
Shuyue Bao, Ping Sun, Jianxin Zhu, Qian Ji, Junheng Liu
Summary: This study proposes an adaptive adjustment method and a dynamic equivalent consumption factor calculation method to solve the problems of interpolation error and dimensional disaster in the optimal control problem for hybrid electric vehicles. The effectiveness of the improved algorithm is verified through practical testing.
Article
Energy & Fuels
Cetengfei Zhang, Quan Zhou, Min Hua, Hongming Xu, Mike Bassett, Fanggang Zhang
Summary: Due to global decarbonization efforts, the demand for maximizing battery lifespan in electrified vehicles, including plug-in hybrid vehicles (PHEV), has increased. This paper proposes a Cuboid Equivalent Consumption Minimization Strategy (C-ECMS) for PHEVs to balance diverse control objectives such as fuel economy, state-of-charge (SoC) control, and battery life. The C-ECMS introduces a new concept of the Hamiltonian matrix and aging factor to enable optimal dual motor control. Experimental results show that the C-ECMS outperforms the standard ECMS in terms of SoC accuracy, fuel consumption, and battery capacity loss.
Article
Green & Sustainable Science & Technology
Yan Wu, Syed Mahfuzul Aziz, Mohammed H. Haque
Summary: This research proposes a novel household energy cost optimisation method by incorporating more realistic variable EV charging characteristics, power export limits, degradation of battery energy storage, and battery salvage revenue. It shows that PV with BES and EV is the most economical configuration for individual households.
Article
Engineering, Mechanical
Yuanbo Zhang, Weida Wang, Changle Xiang, Chao Yang, Haonan Peng, Chao Wei
Summary: Braking energy recovery is a crucial technology for electric vehicles' economic performance. However, finding the optimal regenerative braking control strategy considering safety, economy, and comfort remains challenging due to the non-linear and multi-objective characteristics of hybrid braking systems. In this study, a swarm intelligence-based predictive regenerative braking control strategy is proposed, which is tested for stability and economy through simulation experiments. Additionally, an equivalent control strategy is suggested to reduce computational complexity.
VEHICLE SYSTEM DYNAMICS
(2022)
Article
Thermodynamics
Lei Hao, Ying Wang, Yuanqi Bai, Qiongyang Zhou
Summary: The paper presents a new application of the BFS algorithm in the EMS of HEVs, showcasing the potential of global optimization and real-time control in reducing fuel consumption. The results demonstrate significant improvements and potential for future research in this area.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Engineering, Mechanical
Pengfei Zou, Fazhan Tao, Zhumu Fu, Pengju Si, Chao Ma
Summary: This paper focuses on the energy management strategy (EMS) of hybrid electric vehicles equipped with fuel cell/battery/supercapacitor, aiming to reduce hydrogen consumption and prolong the lifespan of power sources. The proposed hierarchical EMS can achieve a balance between the lifespan of power sources and fuel economy of vehicles. Results indicate the effectiveness of the method has been verified.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING
(2022)
Article
Green & Sustainable Science & Technology
Z. Chen, Y. Liu, M. Ye, Y. Zhang, G. Li
Summary: Hybrid electric vehicles use a combination of fuel and electric power as power supply to improve fuel economy, requiring a well-designed energy management strategy to cope with the complexity of power distribution. Equivalent consumption minimisation strategy, with the use of an equivalent factor, is a promising technique for achieving real-time fuel economy optimisation and is classified based on its dependence on either online computation or offline pre-computation.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
Article
Energy & Fuels
Mingliang Bai, Wenjiang Yang, Ruopu Zhang, Marek Kosuda, Peter Korba, Michal Hovanec
Summary: Hybrid-electric propulsion system (HEPS) is gaining attention in UAVs for its potential to reduce fuel consumption and emissions. This study introduces a fuzzy logic control-equivalent consumption minimum strategy (FLC-ECMS) that improves energy management in HEPS. Simulation tests show that HEPS-equipped hybrid UAVs can significantly decrease fuel consumption and emissions, while maintaining battery state of charge (SOC) and reducing SOC difference. This research provides insights into optimal energy management for HEPS in UAVs, highlighting the importance of UAVs in reducing environmental impacts.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Chemistry, Multidisciplinary
Gulnora Yakhshilikova, Sanjarbek Ruzimov, Ethelbert Ezemobi, Andrea Tonoli, Nicola Amati
Summary: This paper investigates the impact of engine transient characteristics on fuel consumption in hybrid electric vehicles and proposes a penalty factor introduced in the controller to optimize engine usage. Through simulation experiments, it is proven that reducing transient engine operation can lead to a decrease in fuel consumption.
APPLIED SCIENCES-BASEL
(2022)
Article
Thermodynamics
Mingyao Yao, Bo Zhu, Nong Zhang
Summary: This paper presents a novel adaptive ECMS method for real-time optimal control of EREVs by transforming the fuel economy problem into convex optimization through variable substitution and polynomial fitting of fuel and battery consumption models. The proposed method achieves close-to-target terminal SOC maintenance, less than 2% difference in fuel economy compared to global optimization EMS, and significant improvements in computational efficiency compared to the shooting method.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Energy & Fuels
Cheng Li, Guangdi Hu, Zhongwen Zhu, Xu Wang, Weihai Jiang
Summary: This paper proposes a neural network-based equivalent factor predictor for real-time prediction of equivalent factors in fuel cell electric vehicles. It also improves the real-time performance of the equivalent consumption minimization strategy. Simulation and experimental results demonstrate that the designed strategy can better maintain battery state of charge and achieve significant energy savings.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Article
Green & Sustainable Science & Technology
Yan Wu, Syed Mahfuzul Aziz, Mohammed H. Haque
Summary: This study proposes a novel modeling approach to minimize the net annual energy cost of a university campus providing EV charging service. Results show that using this method can reduce peak demand and net annual energy cost, with the reduction increasing with EV penetration.
Article
Energy & Fuels
Zeyu Chen, Hao Zhang, Rui Xiong, Weixiang Shen, Bo Liu
Summary: This study reveals the impact of price fluctuations on optimal control strategies, proposes a PHEVs energy management strategy taking price fluctuations into consideration, and achieves better energy economy through optimization algorithms.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Engineering, Chemical
Dapai Shi, Shipeng Li, Kangjie Liu, Yun Wang, Ruijun Liu, Junjie Guo
Summary: Under the dual-carbon goal, research on energy conservation and emission reduction of new energy vehicles has once again become a hot topic. This study proposes an adaptive energy management strategy for plug-in hybrid electric vehicles (PHEVs) to improve fuel economy based on intelligent prediction of driving cycles. Simulation results show that the proposed strategy achieves a 9.85% higher fuel saving rate compared to the rule-based strategy and a 5.30% higher rate compared to the ECMS strategy without prediction, further enhancing the fuel saving potential of PHEVs.
Article
Thermodynamics
Likang Fan, Yufei Wang, Hongqian Wei, Youtong Zhang, Pengyu Zheng, Tianyi Huang, Wei Li
Summary: The paper presents a real-time EMS for PHEVs based on adaptive regulation of multiple parameters, achieving optimized charge depletion stage and improving adaptability and efficiency. The use of ECMS replaces traditional rules, allowing for real-time optimal solutions and addressing torque distribution challenges.