Article
Engineering, Electrical & Electronic
Sebastien Delprat, Mohamed Riad Boukhari
Summary: This paper investigates the predictive Equivalent Consumption Minimization Strategy for hybrid vehicle energy management. It formulates the energy management as a receding optimization problem to determine torque split between the internal combustion engine and electric machine. By exploiting the slow dynamic distribution and rational tuning of algorithm parameters, the strategy allows for controlling state of charge and achieving low fuel consumption.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
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
Thermodynamics
Dapai Shi, Kangjie Liu, Yun Wang, Ruijun Liu, Shicheng Li, Yanzhao Sun
Summary: The study proposed an adaptive equivalent minimum fuel consumption strategy (A-ECMS) to optimize the energy control strategy of PHEVs, which significantly improved fuel economy by reducing vehicle fuel consumption by 7% under three times WLTC driving condition compared to the CD/CS strategy.
ADVANCES IN MECHANICAL ENGINEERING
(2021)
Article
Energy & Fuels
Xinyou Lin, Jiajin Zhang
Summary: This paper proposes a battery aging-aware energy management strategy with dual-state feedback control based on multiple neural network learning algorithms to achieve real-time control in random driving cycles and prolong battery life for plug-in hybrid electric vehicles (PHEV). By combining offline optimization control results and neural network training, the strategy effectively reduces the life cycle cost by introducing dual-state feedback control.
JOURNAL OF ENERGY STORAGE
(2022)
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
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
Mathematics
Xiangqing Zhao
Summary: This paper investigates computer virus transmission through mathematical modeling and proposes improved models and optimal control systems for reducing network detoxification costs and the proportion of broken-out nodes. Numerical simulations are conducted to validate the effectiveness of the theoretical analyses.
Article
Energy & Fuels
Kai Deng, Hujun Peng, Steffen Dirkes, Jonas Gottschalk, Cem Uenluebayir, Andreas Thul, Lars Lowenstein, Stefan Pischinger, Kay Hameyer
Summary: This paper proposes a new causal energy management strategy based on PMP for developing railway vehicles powered by fuel cell and battery systems, which was tested and validated for performance and real-time capability. The strategy achieves an optimal SoC trajectory without the need for complete rail track information and demand prediction.
Article
Energy & Fuels
Alberto Broatch, Pablo Olmeda, Benjamin Pla, Amin Dreif
Summary: Energy management is crucial for electrified vehicles and directly affects the efficiency, durability, driveability, and safety of the vehicle powertrain. Due to the complexity of the powertrain components, control algorithms and numerical methods have been developed to optimize the operation of hybrid powertrains. In this study, an equivalent consumption minimization strategy (ECMS) is used to predict the impacts of control actions and minimize associated costs.
Article
Engineering, Marine
Yuequn Ge, Jundong Zhang, Kunxin Zhou, Jinting Zhu, Yongkang Wang
Summary: This paper analyzes a hybrid power system containing a fuel cell and proposes an improved scheme involving the replacement of a single energy storage system with a hybrid energy storage system. An efficient energy management system based on the equivalent consumption minimization strategy is proposed to achieve a reasonable power distribution and stable operation. The proposed strategy outperforms the state-based and fuzzy logic-based EMS in terms of stabilizing the hybrid power system and reducing hydrogen consumption.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Information Systems
Dongdong Chen, Tie Wang, Tianyou Qiao, Tiantian Yang, Zhiyong Ji
Summary: This study proposes an adaptive equivalent consumption minimization strategy (A-ECMS) based on driving cycle recognition for a parallel hybrid electric vehicle (HEV). By training a neural network for accurate driving cycle recognition, the optimal equivalent factor is selected for the current driving cycle. Simulation results show that compared to logic-based EMS, A-ECMS can reduce fuel consumption and improve battery state of charge in different driving cycles.
Article
Mathematics, Interdisciplinary Applications
Parthasakha Das, Samhita Das, Pritha Das, Fathalla A. Rihan, Muhammet Uzuntarla, Dibakar Ghosh
Summary: This article develops and analyzes a non-linear mathematical model of tumor-immune interactions with combined therapeutic drug and treatment controls. Optimal treatment strategies are established to maximize immune-effector cell number, minimize cancer cell number, and reduce detrimental effects caused by drugs. Sensitivity analysis and cost-effectiveness analysis are performed to identify important parameters and determine the most cost-effective therapeutic strategy. Numerical results validate analytical findings, showing that combinatorial drug therapy can alleviate cancer cells under different scenarios.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Engineering, Mechanical
R. Vignesh, A. Harikrishnan, Bragadeshwaran Ashok, M. Senthil Kumar, Rajan Malewar
Summary: Hybrid electric powertrains are the optimal choice for solving the pollution and energy crisis caused by automotive vehicles. This research incorporates intelligent control and adaptive equivalent consumption minimization strategy to improve power distribution and enhance performance and fuel efficiency of electric vehicles. Experimental results show that the suggested approach outperforms other methods in battery and energy usage as well as emissions reductions.
JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING
(2023)
Article
Energy & Fuels
Shailesh Hegde, Angelo Bonfitto, Renato Galluzzi, Luis M. Castellanos Molina, Nicola Amati, Andrea Tonoli
Summary: This study introduces a novel formulation of the ECMS method in the P0 system that takes into account the power loss map of the belt drive system (BDS) and the characteristic maps of the electric machine (EM) and internal combustion engine (ICE). By using a genetic algorithm to adjust the equivalence factors of the ECMS, the proposed method aims to reduce fuel usage and CO2 emissions. Experimental results show that the use of the BDS power loss maps in the ECMS method achieved CO2 savings of 1.1 and 0.9 [g/km] in the WLTP driving cycle.
Article
Chemistry, Analytical
Jianhua Guo, Zhiqi Guo, Liang Chu, Di Zhao, Jincheng Hu, Zhuoran Hou
Summary: This paper proposes a novel dual-adaptive equivalent consumption minimization strategy (DA-ECMS) for the complex multi-energy system in 4WD PHEV. By introducing future driving condition categories, the strategy optimizes the management of the multi-energy system and improves the economy, unlocking the energy-saving potential.