Next Article in Journal
Streams Analysis for Better Air Quality: The German Lead City Program Assessed by the Policy Package Approach and the Multiple Streams Framework
Next Article in Special Issue
Stochastic Drift Counteraction Optimal Control of a Fuel Cell-Powered Small Unmanned Aerial Vehicle
Previous Article in Journal
Power Hardware-in-the-Loop: Response of Power Components in Real-Time Grid Simulation Environment
Previous Article in Special Issue
Power Split Supercharging: A Mild Hybrid Approach to Boost Fuel Economy
Article

Energy Optimization of Electric Vehicles by Distributing Driving Power Considering System State Changes

1
School of Mechanical Engineering, Sungkyunkwan University, Suwon 16419, Korea
2
Central R&D Center, Mando Corporation, Seongnam 13486, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Islam Safak Bayram
Energies 2021, 14(3), 594; https://doi.org/10.3390/en14030594
Received: 21 December 2020 / Revised: 18 January 2021 / Accepted: 22 January 2021 / Published: 25 January 2021
In a battery-electric vehicle, a representative electric vehicle, there is a growing demand for performance and one-charge mileage improvement. As an alternative to such improvements, the capacity of the battery has been increased; however, due to the corresponding increase in the weight of the battery and the limited space in the vehicle, increasing the capacity of the battery also has limitations. Therefore, researches are being actively conducted to improve system operation efficiency to overcome such limitations. This paper proposes a distributing method of the driving forces to a battery-powered electric shuttle bus for last-mile mobility equipped with the decentralized driving system while taking into account voltage changes of the input terminals due to changes in the battery charge. The system operation efficiency changes were compared and evaluated by performing energy consumption analysis using ‘Manhattan Bus Driving Cycle’ at low voltage condition (SOC 20%). Various analyzes were performed and compared, such as the uniform distribution method of driving forces of the front and rear wheels (Uniform), the optimization method without considering the input terminal voltage change (Vnorm = 90 V), and the optimization method considering the input terminal voltage change (Vdclink). As a result, it shows that the proposed algorithm can improve 6.0% compared to the conventional uniform driving force distribution method (Uniform). Moreover, it shows that the real-time optimization method without considering the input voltage change (Vnorm = 90 V) can improve 5.3% compared to the uniform distribution method. The proposed method can obtain an additional 0.7% increase in total cost compared to the existing optimization method, which shows that the vehicle system has cost-effectiveness by reducing the battery capacity required to achieve the same mileage. View Full-Text
Keywords: driving force distribution; decentralized traction system; 4WD electric vehicle; energy efficiency; traction control; efficiency optimization driving force distribution; decentralized traction system; 4WD electric vehicle; energy efficiency; traction control; efficiency optimization
Show Figures

Figure 1

MDPI and ACS Style

Jang, I.-G.; Lee, C.-S.; Hwang, S.-H. Energy Optimization of Electric Vehicles by Distributing Driving Power Considering System State Changes. Energies 2021, 14, 594. https://doi.org/10.3390/en14030594

AMA Style

Jang I-G, Lee C-S, Hwang S-H. Energy Optimization of Electric Vehicles by Distributing Driving Power Considering System State Changes. Energies. 2021; 14(3):594. https://doi.org/10.3390/en14030594

Chicago/Turabian Style

Jang, In-Gyu, Chung-Seong Lee, and Sung-Ho Hwang. 2021. "Energy Optimization of Electric Vehicles by Distributing Driving Power Considering System State Changes" Energies 14, no. 3: 594. https://doi.org/10.3390/en14030594

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop