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

Abstract

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.

Open Innovations for Tourism Logistics Design: A Case Study of a Smart Bus Route Design for the Medical Tourist in the City of Greater Mekong Subregion

“…A battery for a longdistance vehicle needs to be considered that has more capacity and power, can travel extremely far, and can supply the final miles of the vehicle's driving range. The vehicle must be able to quickly locate the battery-charging station [61]. However, because using clean energy is less expensive than conventional energy in the beginning, operators will be able to minimize energy expenses by investing in cars that employ clean energy technology.…”

A Novel Energy-Efficiency Optimization Approach Based on Driving Patterns Styles and Experimental Tests for Electric Vehicles

“…In order to propose an optimization algorithm for the driving patterns to achieve maximum efficiency energy, it is important to understand the traction management and the energy consumption flow, from the battery to the EV wheels. In addition, the power conditions and limitations of battery discharge EV during its operation were considered as studies showed in [43,44]. Figure 8 shows an overall diagram where each subsystem is interconnected.…”

Intelligent Energy Management System Evaluation of Hybrid Electric Vehicle Based on Recurrent Wavelet Neural Network and PSO Algorithm

“…Transportation via fuel cell electric vehicles (FCEVs), fuel cell hybrid electric vehicles (FCHEVs) and battery electric vehicles (BEVs) have gained popularity. However, BEVs that use the battery pack as the main power has some drawbacks such as the short driving range [2], the battery requires hours to fully charge [3] and high cost and weight of BEVs due to their large battery packs [4]. Meanwhile, FCEVs have also some disadvantages such as dynamic response is slow as well as a high hydrogen cost, and the inability to recharge by the principle of regenerative braking energy [5].…”