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Subject: search.filters.subject.electric vehicle (EV)

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    Quantitative Assessment of EV Energy Consumption: Applying Coast Down Testing to WLTP and EPA Protocols
    (2025-07-01)
    Phophongviwat, Teeraphon
    ;
    Poopanya, Piyawong
    ;
    Sivalertporn, Kanchana
    This study presents a comprehensive methodology for evaluating electric vehicle (EV) energy consumption by integrating coast down testing with standardized chassis dynamometer protocols under WLTP Class 3b and EPA driving cycles. Coast down tests were conducted to determine road load coefficients—critical for replicating real-world resistance profiles on a dynamometer. Energy usage data were measured using On-Board Diagnostics II (OBD-II) and dynamometer measurements to assess power flow from the battery to the wheels. The results reveal that OBD-II consistently recorded higher cumulative energy usage, particularly under urban driving conditions, highlighting limitations in dynamometer responsiveness to transient loads and regenerative events. Notably, the WLTP low-speed cycle exhibited a significantly lower efficiency of 62.42%, with nearly half of the battery energy consumed by non-propulsion systems. In contrast, the EPA cycle demonstrated consistently higher efficiencies of 84.52% (low-speed) and 93.00% (high-speed). Interestingly, high-speed efficiencies between WLTP and EPA were nearly identical, despite differences in total energy consumption. These findings underscore the importance of aligning test protocols with actual driving conditions and demonstrate the effectiveness of combining coast down data with real-time diagnostics for robust EV performance assessments.
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    Fuzzy Analytical Hierarchy Process for Strategic Decision Making in Electric Vehicle Adoption
    (2023-04-01)
    Aungkulanon, Pasura
    ;
    Atthirawong, Walailak
    ;
    Luangpaiboon, Pongchanun
    In response to the requirement to address the global climate crisis in urban areas caused by the logistics sector, an increasing number of governments around the world have begun aggressive strategic actions to encourage manufacturers and consumers to adopt electric vehicle (EV) technology. One of the most beneficial aspects of driving an EV is that it reduces pollution while also reducing the use of fossil fuels, as well as improving public health by improving local air quality. Nevertheless, the level of EV adoption differs significantly across markets and geographies. EV adoption barriers slow the overall rate of electric mobility. This study ranks a list of obstacles and sub-hindrances to the adoption of electric vehicles in Thailand using the Fuzzy Analytical Hierarchy Process (FAHP), a Multi-Criteria Decision Making (MCDM) technique. The results showed that infrastructure policy barrier (A), which had the highest weight of 0.6058, was the biggest barrier to EV adoption, followed by technological barrier (B) with a weight of 0.2657, and then by market barrier with a weight of 0.1285. Insufficient charging infrastructure network (A3), lack of proper government support/incentives and collaboration (A1), insufficient electric power supply (A2), high capital cost (C3), and EV charging time (B3) were key sub-barriers to EV adoption in Thailand. Decision Making Systems (DMS) have additionally been created to assist executives in making decisions about the aforementioned barriers. The DMS is based on the concept of computer-aided decision making in that it allows for direct user interaction, analysis, and the ability to change circumstances and the decision-making process based on the executives’ own experience and abilities. Thus, the findings of this study aid in the formulation of market strategies for relevant stakeholders and shed light on potential policy responses.
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    EVs Charging Power Control Participating in Supplementary Frequency Stabilization for Microgrids: Uncertainty and Global Sensitivity Analysis
    (2021-01-01)
    Jamroen, Chaowanan
    ;
    Ngamroo, Issarachai
    ;
    Dechanupaprittha, Sanchai
    Electric vehicle (EV) potential has broadly been highlighted in providing ancillary services in a microgrid, such as grid reserve and regulation support. However, uncertain behaviors of EV charging raise crucial concerns for both the utilities and EV owners. In this paper, the impacts of EV charging uncertainties for EV charging power control participating in supplementary frequency stabilization are assessed separately based on the two perspectives, i.e., power capacity for the utility perspective and expected EV energy for the EV owner perspective. On the one hand, the power capacity accessed by the utility directly relates to the stabilization capability, which depends on the number of EVs that are willing to participate in the frequency stabilization program and the rated charging power of EV. On the other hand, the variance of expected EV energy realized by the EV owners is considered in terms of the remaining state of charge (SoC), energy capacity, and available charging time. Besides, a variance-based global sensitivity analysis (GSA) is essentially applied to identify the influential parameters of these uncertainties. The simulation studies are conducted using a microgrid environment via DIgSILENT Powerfactory software to reveal such impacts of EV charging uncertainties based on the two perspectives. The results indicate that the number of participating EVs is the most influential parameter for frequency stabilization capability, followed by the rated charging power of EV. From the EV owner's perspective, the energy capacity is the dominant parameter affecting the expected EV energy variance, followed by the remaining energy and available charging time.
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    Short range wireless power charging on small electric vehicles
    (2014-12-23)
    Khan-Ngern, Werachet
    ;
    Zenkner, Heinz
    This paper presents the research work focusing on charging the energy via the air to a small electric vehicle (EV). This work shows not only the possibility of wireless power charging, but also the electromagnetic compatibility (EM C) issue is taken into account. The charging system is described and set up using the resonance coupling effect and single-ended primary-inductor converter (SEPIC) for a low DC power charging The transmitting power is applied at a frequency of 6.78 M Hz across a gap in the short range between 100 mm to 200 mm The experimental results show that the maximum efficiency up to 80 % were acheived to charge to a three wheel electric scooter 36 V system up to 14 W. The wireless char ging has been studied on radiated emission during charging mode at transmitter, receivers and at the gap between transmitter and receiver.
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    Wireless power charging on electric vehicles
    (2014-10-15)
    Khan-Ngern, Werachet
    ;
    Zenkner, Heinz
    This paper presents wireless power charging to a electric vehicle (EV) focusing on resonant topology. The charging system is described and set up using the resonance coupling effect and single-ended primary-inductor converter (SEPIC) for a low DC charging. The transmitting power is applied at a frequency of 6.78 MHz across a gap in the short range between 10 cm to 20 cm. The experimental results show that the maximum efficiency up to 80 % from transmitter to receiver. The EV charging using wireless charging has been confirmed with park and ride demonstration at 10 W power charging scale. The real time of wireless power charging can be monitored via Zigbee system. This work shows not only the possibility of wireless power charging, but also the electromagnetic compatibility (EMC) issue is taken into account.