Range anxiety reduction in battery-powered vehicles

Faraj, Mahmoud; Basir, Otman

doi:10.1109/itec.2016.7520190

Cited by 30 publications

(12 citation statements)

References 3 publications

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“…This is also possible considering that on Saturday and on Sunday the overall consumption is lower compared to the weekdays. The charging probability is dependent on the human behaviour, which is affected by range anxiety due to vehicle range, available charging infrastructure, range requirements of drivers [36]- [40]. In the current model the probability of charging of the EVs is included as SOC and driving distance dependent, through the plug-in ratio at home of the EVs.…”

Section: Ev Charging Load Modellingmentioning

confidence: 99%

“…5) Plug-in rate at home: The Japanese statistics conducted by Nissan on 10000 24 kWh Nissan EVs derived the probability of charging at home of the commuters, based on the final SOC of the daily distance driven. Considering an individual user, the range anxiety is difficult to predict, because the users tend to charge their vehicles even when it is not necessary [36]. Differently, considering large groups of EVs, as done by Nissan, it is possible to derive a relation between the plugin rate at home and the SOC, as reported in Fig.…”

Section: Ev Charging Load Modellingmentioning

confidence: 99%

See 1 more Smart Citation

Grid Loading Due to EV Charging Profiles Based on Pseudo-Real Driving Pattern and User Behavior

Calearo

Thingvad

Suzuki

et al. 2019

IEEE Trans. Transp. Electrific.

115

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Section: Ev Charging Load Modellingmentioning

confidence: 99%

Section: Ev Charging Load Modellingmentioning

confidence: 99%

Grid Loading Due to EV Charging Profiles Based on Pseudo-Real Driving Pattern and User Behavior

Calearo

Thingvad

Suzuki

et al. 2019

IEEE Trans. Transp. Electrific.

115

View full text Add to dashboard Cite

show abstract

“…When the detected BEV range remaining is close to the safety buffer range for the trip, the BEV should give guidance on solving the range anxiety. One solution has been proposed in [6] that helps the driver to follow the energy-optimized travelling route, which could relieve the range anxiety. By recording the personal attributes and behaviors, the BEV can generate a specific trip solution for each driver.…”

Section: Supposed Methods Of Helping With Range Anxietymentioning

confidence: 99%

“…Mahmoud Faraj and Otman Basir [6] proposed a path arrangement model based on battery capability and energy cost analysis. The model compares the battery capacity of the BEV with the least energy cost of a round trip to the charging station.…”

Section: Introductionmentioning

confidence: 99%

Investigation on Range Anxiety and Safety Buffer of Battery Electric Vehicle Drivers

Yuan

Hao

et al. 2018

Journal of Advanced Transportation

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Drivers tend to have more range anxiety compared with driving traditional fuel vehicles if they are driving battery electric vehicle (BEV) with a long trip. Range anxiety could potentially have negative effect on driver's emotions and behaviors. In order to understand this behavior and improve the related safety issues, this paper will focus on BEV drivers' study in China. A survey on BEV drivers' actual range anxiety as well as the effect of range anxiety on drivers' behaviors is conducted in this research. Levels of feelings and attitudes of the interviewees are quantized with Likert scales using mathematical tools of the relationship. Safety buffer is defined as a measurement of the period given range anxiety starting to significantly intervene in driver's operation. The research reveals the proportional quotative relationship between BEV drivers' safety buffer and the mileage of trip. Factors, including driving experience, satisfactory level of recharge accessibility, and resistibility to emotions, are found to be significant contributing factors to influence the perceived range anxiety level of BEV drivers. This research will provide implications to the future study on the interface design of BEV.

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“…However, the mass adoption of EVs has been impeded by limited availability of charging infrastructure, long charging time, and limited travel range per charge. These can cause driver's concern which is called "range anxiety" [9]. There have been efforts to overcome these barriers by advancing battery technology [10] and investing in electric charging infrastructure [11].…”

mentioning

confidence: 99%

Connected Cooperative Ecodriving System Considering Human Driver Error

Wang

et al. 2018

IEEE Trans. Intell. Transport. Syst.

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In recent years, eco-friendly driving or ecodriving technologies are being developed to assist human drivers to achieve maximum fuel/energy efficiency in different driving conditions. Enhanced by V2X wireless communications, connected ecodriving is expected to be very promising in reducing transportation-related fossil fuel consumption as well as pollutant emissions. Besides, the deployment of electric vehicles (EVs) also has great potential in reducing greenhouse gas emissions due to the use of batteries as the sole energy source. Although recent research shows that significant energy savings can be achieved with the aid of ecodriving systems in real-world driving, there have been very few research efforts that consider human driver error, especially for electric vehicle (EV) driving. In this paper, a connected cooperative ecodriving system for energyefficient driving that considers human driver error is designed and evaluated with an EV energy consumption model. Realworld driving data were collected and used to evaluate system performance in terms of energy consumption. The simulation and numerical analysis shows that an average of 12% energy savings can be achieved by the proposed system that considers human driver error comparing with the conventional ecodriving system without considering driver error.

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Range anxiety reduction in battery-powered vehicles

Cited by 30 publications

References 3 publications

Grid Loading Due to EV Charging Profiles Based on Pseudo-Real Driving Pattern and User Behavior

Grid Loading Due to EV Charging Profiles Based on Pseudo-Real Driving Pattern and User Behavior

Investigation on Range Anxiety and Safety Buffer of Battery Electric Vehicle Drivers

Connected Cooperative Ecodriving System Considering Human Driver Error

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