A Comprehensive Review of Energy Management Strategies in Hybrid Electric Vehicles: Comparative Analysis and Challenges

被引:1
作者
Tella, Vaishnavi Chandra [1 ]
Alzayed, Mohamad [2 ]
Chaoui, Hicham [2 ]
机构
[1] Texas Tech Univ, Dept Elect & Comp Engn, Lubbock, TX 79409 USA
[2] Carleton Univ, Dept Elect, Intelligent Robot & Energy Syst Res Grp IRES, Ottawa, ON K1S 5B6, Canada
关键词
Batteries; Fuels; Energy management; Dynamic programming; Hybrid electric vehicles; Engines; Electric motors; Optimization; Hybrid power systems; Combustion; Climate change; Energy management strategies; hybrid electric vehicles; plug-in hybrid; offline and online control strategies; rule-based; optimization-based; deep learning; reinforcement learning; LEARNING-BASED ENERGY; POWER MANAGEMENT; DIFFERENTIAL EVOLUTION; TORQUE DISTRIBUTION; OPTIMIZATION; MODEL; MINIMIZATION; SYSTEMS; ARCHITECTURE; OPERATION;
D O I
10.1109/ACCESS.2024.3509737
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
As air pollution, greenhouse gases, and global warming worsen, finding clean energy sources is critical. Renewable energy is a promising solution, especially in the transportation sector, which consumes significant energy. Hybrid electric vehicles (HEVs), combining an internal combustion engine and an electric battery, are key to reducing fossil fuel use and mitigating environmental harm. Effectively managing power distribution between these sources to enhance efficiency and minimize fuel consumption is crucial, known as an Energy Management Strategy (EMS). This article provides an overview of various EMS approaches for HEVs, analyzing their advantages and disadvantages. Rule-based strategies offer simplicity, optimization-based strategies provide superior performance, and advanced techniques like machine learning promise significant improvements. Current trends include integrating sophisticated sensors, data analytics, and artificial intelligence for real-time decision-making. Future directions aim at robust EMS frameworks integrating smart grid technologies and vehicle-to-everything (V2X) communication. The article reviews EMS methodologies, comparing their strengths and weaknesses, and discusses the main challenges and future trends in energy management for hybrid electric vehicles.
引用
收藏
页码:181858 / 181878
页数:21
相关论文
共 159 条
[1]   A multivariable output neural network approach for simulation of plug-in hybrid electric vehicle fuel consumption [J].
Adedeji, Bukola Peter .
GREEN ENERGY AND INTELLIGENT TRANSPORTATION, 2023, 2 (02)
[2]   Q-learning based control for energy management of series-parallel hybrid vehicles with balanced fuel consumption and battery life [J].
Ahmadian, Saeid ;
Tahmasbi, Mohammad ;
Abedi, Reza .
ENERGY AND AI, 2023, 11
[3]   Different architectures and modes of operation of HEV based on permanent magnet-electric variable transmission with rule-based and fuzzy logic global control strategy [J].
Ahmed, Abdelsalam ;
Cui, Shumei .
INTERNATIONAL JOURNAL OF ELECTRIC AND HYBRID VEHICLES, 2012, 4 (01) :69-92
[4]   Configurable Harris Hawks Optimisation for Application Placement in Space-Air-Ground Integrated Networks [J].
Akhter, Nasrin ;
Mahmud, Redowan ;
Jin, Jiong ;
But, Jason ;
Ahmad, Iftekhar ;
Xiang, Yong .
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, 2024, 21 (02) :1724-1736
[5]   Particle Swarm Optimization of Coupled Electromechanical Systems [J].
Al-Aawar, N. ;
Hijazi, T. M. ;
Arkadan, A. A. .
IEEE TRANSACTIONS ON MAGNETICS, 2011, 47 (05) :1314-1317
[6]   EM-TFL Identification for Particle Swarm Optimization of HEV Powertrain [J].
Al-Aawar, N. ;
Hijazi, T. M. ;
Arkadan, A. A. .
2009 IEEE INTERNATIONAL ELECTRIC MACHINES & DRIVES CONFERENCE, VOLS 1-3, 2009, :109-112
[7]  
Anderson T. A., 2008, P IEEE VEH POW PROP, P1
[8]   Optimal Energy Management of Hybrid Storage Systems Using an Alternative Approach of Pontryagin's Minimum Principle [J].
Bao-Huy Nguyen ;
Thanh Vo-Duy ;
Ta, Minh C. ;
Trovao, Joao Pedro F. .
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION, 2021, 7 (04) :2224-2237
[9]   Real-Time Energy Management of Battery/Supercapacitor Electric Vehicles Based on an Adaptation of Pontryagin's Minimum Principle [J].
Bao-Huy Nguyen ;
German, Ronan ;
Trovao, Joao Pedro F. ;
Bouscayrol, Alain .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2019, 68 (01) :203-212
[10]  
Baumann B., 1998, SAE Tech. Paper 981061, DOI [10.4271/981061, DOI 10.4271/981061]