Optimization Effect of the Improved Power System Integrating Composite Motors on the Energy Consumption of Electric Vehicles

被引:1
作者
Jia, Lijun [1 ]
机构
[1] Henan Mech & Elect Vocat Coll, Sch Aeronaut, Zhengzhou 451191, Peoples R China
关键词
composite motor; improved power system; electric vehicles; energy consumption; ENGINE VEHICLES; TECHNOLOGIES; BENEFITS;
D O I
10.3390/wevj14090257
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The multi-power source coupled transmission system is a high-performance and energy-saving potential power transmission system, and most of the commonly used pure electric vehicles in the market that use multi-power source coupled drive adopt the motor dual-axis distributed independent drive scheme. The configuration design method for multi-power source fusion hybrid systems mainly focuses on the search and selection of power split hybrid systems based on planetary gear mechanisms. But it has not yet covered the configuration design of transmission systems, resulting in a lack of universal expression and generation methods for the configuration of multi-power source fusion hybrid systems in pure electric vehicles. Therefore, to solve the configuration optimization design problem of a dual-motor single-planetary-array power system, an improved general matrix topology design method is proposed to generate all feasible topology structures. And energy consumption, economy, and the dynamic performance of alternative configurations are optimized and simulated through the control strategy based on a dynamic programming algorithm. Under comprehensive testing conditions, 25 alternative options that met the screening criteria were selected, and, ultimately, five optimized configuration options were obtained. Configuration 1 has the best economy, reducing energy consumption by about 6.3%and increasing driving range by about 6.7%. Its 0-100 km/h acceleration time is about 31.4% faster than the reference configuration. In addition, the energy consumption economy during actual driving is almost the same as the theoretical optimal energy consumption economy, with a difference of only 0.3%. The success of this study not only provides an innovative method for optimizing the configuration of dual-motor single-row star train power systems, but also has a positive impact on improving energy utilization efficiency, reducing energy consumption, and improving the overall performance of electric vehicles.
引用
收藏
页数:16
相关论文
共 22 条
[1]  
Alateef S., 2022, European Workshop on Performance Engineering, P37
[2]   Comparison of the Overall Energy Efficiency for Internal Combustion Engine Vehicles and Electric Vehicles [J].
Albatayneh, Aiman ;
Assaf, Mohammad N. ;
Alterman, Dariusz ;
Jaradat, Mustafa .
ENVIRONMENTAL AND CLIMATE TECHNOLOGIES, 2020, 24 (01) :669-680
[3]   Synergy and co-benefits of reducing CO2 and air pollutant emissions by promoting electric vehicles-A case of Shanghai [J].
Alimujiang, Adila ;
Jiang, Ping .
ENERGY FOR SUSTAINABLE DEVELOPMENT, 2020, 55 :181-189
[4]   Electric vehicle routing problem with machine learning for energy prediction [J].
Basso, Rafael ;
Kulcsar, Balazs ;
Sanchez-Diaz, Ivan .
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2021, 145 :24-55
[5]   A Review of Heavy-Duty Vehicle Powertrain Technologies: Diesel Engine Vehicles, Battery Electric Vehicles, and Hydrogen Fuel Cell Electric Vehicles [J].
Cunanan, Carlo ;
Tran, Manh-Kien ;
Lee, Youngwoo ;
Kwok, Shinghei ;
Leung, Vincent ;
Fowler, Michael .
CLEAN TECHNOLOGIES, 2021, 3 (02) :474-489
[6]   In-Wheel Motor Drive Systems for Electric Vehicles: State of the Art, Challenges, and Future Trends [J].
Deepak, Kritika ;
Frikha, Mohamed Amine ;
Benomar, Yassine ;
El Baghdadi, Mohamed ;
Hegazy, Omar .
ENERGIES, 2023, 16 (07)
[7]   Electricity demand and carbon emission in power generation under high penetration of electric vehicles. A European Union perspective [J].
Gryparis, Emmanouil ;
Papadopoulos, Perikles ;
Leligou, Hellen C. ;
Psomopoulos, Constantinos S. .
ENERGY REPORTS, 2020, 6 :475-486
[8]   Power system decarbonization: Impacts of energy storage duration and interannual renewables variability [J].
Jafari, Mehdi ;
Korpas, Magnus ;
Botterud, Audun .
RENEWABLE ENERGY, 2020, 156 :1171-1185
[9]   Coordinating Flexible Demand Response and Renewable Uncertainties for Scheduling of Community Integrated Energy Systems With an Electric Vehicle Charging Station: A Bi-Level Approach [J].
Li, Yang ;
Han, Meng ;
Yang, Zhen ;
Li, Guoqing .
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2021, 12 (04) :2321-2331
[10]   Estimation of energy consumption of electric vehicles using Deep Convolutional Neural Network to reduce driver's range anxiety [J].
Modi, Shatrughan ;
Bhattacharya, Jhilik ;
Basak, Prasenjit .
ISA TRANSACTIONS, 2020, 98 :454-470