ABSTRACT
This paper studied the influence of various factors on range anxiety of electric vehicle drivers, and proposed a prediction model of anxiety range based on historical driving data of electric vehicle drivers. The model USES the particle swarm algorithm to optimize the BP neural network that PSO - BP neural network, BP neural network for predicting model of slow convergence speed, and easy to fall into local optimum problem, BP neural network are optimized by the particle swarm optimization (PSO) algorithm to update of all the weight and improve the connection layer in the forecast for the current range of anxiety in the electric car driver, Based on data and experience, the influencing factors that are positively correlated with driver's range anxiety are selected from real data to extract the influencing factors of driver's range anxiety. The predicted anxiety mileage can directly show the current driver's range anxiety, and can also be differentiated by a specific algorithm, which can provide theoretical and data support for future related applications.
- Franke T, Neumann I, Bühler F, Experiencing Range in an Electric Vehicle: Understanding Psychological Barriers. Applied Psychology, 2012, 61(3): 368-391Google Scholar
- Yussof H, Miskon M F, Hanifah R A, Electric Vehicle Battery Modelling and Performance Comparison in Relation to Range Anxiety. Procedia Computer Science, 2015, 76: 250-256.Google ScholarCross Ref
- King C, Griggs W, Wirth F, Using a car sharing model to alleviate electric vehicle range anxiety. 2013: 130-135.Google Scholar
- Neubauer J, Wood E. The impact of range anxiety and home, workplace, and public charging infrastructure on simulated battery electric vehicle lifetime utility. Journal of Power Sources, 2014, 257(3): 12-20.Google ScholarCross Ref
- Skippon S, Garwood M. Responses to battery electric vehicles: UK consumer attitudes and attributions of symbolic meaning following direct experience to reduce psychological distance. Transportation Research Part D : Transport & Environment, 2011, 16 (7): 525-531.Google Scholar
- Ashfaq Muhammad, Butt Osama, Selvaraj Jeyraj, Rahim Nasrudin. Assessment of electric vehicle charging infrastructure and its impact on the electric grid: A review. International Journal of Green Energy, 2021, 18(7).Google Scholar
- Gao H, Kang Z, Lv G, Research on Electric Vehicle Energy Consumption Forecast. Automotive Digest (Chinese), 2021(5):8-13.Google Scholar
- Rodgers L, Zoepf S, Prenninger J. Analysing the Energy Consumption of the BMW Active Field Trial Vehicles with Application to Distance to Empty Algorithms. Transportation Research Procedia, 2014, 4(2014): 42-54.Google ScholarCross Ref
- Lee J T, Kwon S, Lim Y, Effect of Air-Conditioning on Driving Range of Electric Vehicle for Various Driving Modes// Asia Pacific Automotive Engineering Conference. 2013.Google Scholar
- Sun U K, Momroe C W, Christensen J, Thermo⁃electrochemical simulations of performance and abuse in 50-Ah automotive cells. Journal of Power Sources, 2014, 268(3): 625-633.Google Scholar
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