Article
Engineering, Electrical & Electronic
Fengqi Zhang, Xiaosong Hu, Teng Liu, Kanghui Xu, Ziwen Duan, Hui Pang
Summary: The paper proposes a computationally efficient energy management approach for parallel HEVs based on MPC framework, predicting velocity and introducing ECMS strategy to optimize torque split and gearshift while balancing fuel economy and drivability. Conducted sensitivity study and devised EF adaptation law for ECMS-based MPC, showing promising computational efficiency and global convergence to fuel economy produced by DP.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Thermodynamics
Hongwen He, Yunlong Wang, Ruoyan Han, Mo Han, Yunfei Bai, Qingwu Liu
Summary: This paper proposes an improved MPC framework for the EMS of PHEB, aiming to achieve optimal energy distribution with increased prediction accuracy and optimized speed sequences. The speed prediction accuracy is improved between two traffic intersections using the PSO method, while the optimal speed sequence is planned in advance when passing through a traffic intersection.
Article
Thermodynamics
Fengqi Zhang, Xiaosong Hu, Reza Langari, Lihua Wang, Yahui Cui, Hui Pang
Summary: An adaptive energy management strategy based on the equivalent consumption minimization strategy (ECMS) framework is developed to optimize gearshift commands and torque distribution for automated parallel hybrid electric vehicles. The methodology utilizes flexible torque requests to simultaneously consider drivability and fuel economy, resulting in improved powertrain optimization and promising fuel efficiency.
Review
Chemistry, Multidisciplinary
Yunfei Cao, Ming Yao, Xiaodong Sun
Summary: With the increasing strain on global energy reserves and the necessity to comply with national carbon emission regulations, fuel efficiency and environmental friendliness in automobiles are gaining importance. Hybrid electric vehicles (HEVs) have been adopted as a reliable choice for improving fuel economy and reducing emissions due to their combination of long cruising range and energy efficiency. Research on energy management strategies for HEVs, focusing on controlling issues while ensuring battery life and meeting requirements for fuel consumption, emissions, and driving performance, has been conducted and various approaches have been proposed. This literature review provides a comprehensive assessment, highlighting contributions and serving as a complete reference for scholars interested in hybrid vehicle development, control, and optimization.
APPLIED SCIENCES-BASEL
(2023)
Article
Thermodynamics
Kai Gao, Pan Luo, Jin Xie, Bin Chen, Yue Wu, Ronghua Du
Summary: This paper proposes an improved energy management strategy for plug-in hybrid electric vehicles (PHEVs) by integrating driving intention and LIDAR data to achieve accurate speed prediction and optimize energy management in real-time.
Article
Engineering, Electrical & Electronic
Maryam Razi, Nikolce Murgovski, Tomas McKelvey, Torsten Wik
Summary: This paper presents an adaptive equivalent consumption minimization strategy (ECMS) and a linear quadratic tracking (LQT) method for optimal power-split control of a combustion engine and an electric machine in a hybrid electric vehicle (HEV). The study models SOC constraints and proposes sub-optimal analytic solutions with convex objective functions. Additionally, the controllers' robustness to measurement noise is considered, with simulation results comparing the effectiveness of the two controllers.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Engineering, Electrical & Electronic
Kyunghwan Choi, Jihye Byun, Sangmin Lee, In Gwun Jang
Summary: In this study, a novel energy management strategy for hybrid electric vehicles (HEVs) is proposed, which considers actual driving conditions to provide near-optimal performance. The strategy defines a near-optimal equivalent factor condition and presents an iterative scheme to adjust this condition. It shows better adaptability to changes in the driving conditions with a smaller loss of optimality.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Chemistry, Analytical
Zhiqi Guo, Liang Chu, Zhuoran Hou, Yinhang Wang, Jincheng Hu, Wen Sun
Summary: This paper proposes a novel energy management strategy (D-ECMS) to improve the economy of four-wheel drive electric vehicles. By coordinating the output proportion of multiple power components, the vehicle achieves better fuel efficiency and driving range while meeting its dynamic performance requirements.
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
Automation & Control Systems
Xiaodong Sun, Yunfei Cao, Zhijia Jin, Xiang Tian, Mingzhou Xue
Summary: In this article, an adaptive energy management strategy based on real-time traffic information is proposed to improve the efficiency of a parallel hybrid electric bus. The system consists of offline and online components, and utilizes velocity characteristic parameters and Markov transition matrices to predict vehicle speed on different road types. The online component incorporates predicted speed and road information into an equivalent consumption minimization strategy for adaptive changes. Simulation studies show the superiority of the proposed strategy in improving fuel economy, and hardware-in-the-loop tests confirm its compatibility with the original design intent.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Iman Shafikhani, Jan Aslund
Summary: The paper derives an analytical solution to the energy management problem for series hybrid electric vehicles by partitioning the positive power demand set into four subsets and deriving a solution for each case separately. The proposed solution includes effective equivalence factor bounds and an adaptive equivalent consumption minimization strategy, demonstrating effectiveness in real-world applications. Simulation results show that the proposed methodology is relatively fast and has satisfactory performance in the presence of drive cycle uncertainty, achieving fuel consumption figures close to optimal benchmarks.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Optics
Xinyi Liu, Hao Zhang, Qiqi Ma, Xin Zhao, Chenqi Di
Summary: This article analyzes the impact of vehicle speed on the quality of visible light communication technology services in vehicle networking. Through analyzing changes in signal-to-noise ratio and channel states, as well as simulating scenarios, the transformation in signal-to-noise ratio in various scenarios has been analyzed.
Article
Computer Science, Information Systems
Heeyun Lee, Suk Won Cha
Summary: This study introduces a reinforcement learning-based approach to determine the equivalent factor in hybrid electric vehicles, indirectly extracted from reinforcement learning results. By combining reinforcement learning with the equivalent consumption minimization strategy, the proposed method achieves near-optimal performance compared to dynamic programming and improves performance compared to existing strategies.
Article
Engineering, Civil
Dajiang Suo, John Moore, Mathew Boesch, Kyle Post, Sanjay E. Sarma
Summary: This paper investigates the security vulnerabilities and defense mechanisms for connected and automated vehicles (CAVs) from an engineering design perspective. It presents a systematic approach to identify and mitigate physical threats that compromise the safety of individual vehicles and cyber threats that disrupt CAV-enabled transportation services. An integrated security engineering process and a multi-layer design framework are introduced to provide traceability and guidance in threat identification and mitigation.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
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)