Simulation of battery energy consumption in an electric car with traction and HVAC model for a given source and destination for reducing the range anxiety of the driver. (15th June 2022)

• Record Type: Journal Article
• Authors: Hariharan, C.; Gunadevan, D.; Arun Prakash, S.; Latha, K.; Antony Aroul Raj, V.; Velraj, R.
• Is Part Of: Energy. Volume 249(2022)
• Publication Date: 2022-06-15
• Subjects: Traction energy -- HVAC -- Solar heat radiation -- Electric vehicles -- Cabin cooling; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2022.123657
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Due to depletion and price hike of fossil fuel, most of the developing and developed countries are shifting to Electric vehicles. The major problem faced by the electric vehicle drivers is the range anxiety for battery charging. For predicting the battery range of electric vehicle, a systematic simulation of both traction and HVAC power consumption is required. In this work, a simulation model has been created in MATLAB to calculate the energy required for traction and HVAC system of the vehicle for a selected source and destination by considering heat entry, orientation and location of the electric vehicle. By using transient simulation model, electrical energy requirement of the vehicle for the trip is calculated and quantified for the given variations of drving cycle, orientation, altitude, ambient temperature along the trip. The simulation is validated by running the electric vehicle in different trips with and without air-conditioning. The average error between the measured and simulated value is less than 2.59% and the average deviation in the range estimation for the different trips considered is 4.09%. This simulated model will be useful for vehicle drivers to forecast the range and decide about battery charging strategy of electric vehicle. Graphical abstract: Image 1 Highlights: This model forecasts the energy consumption of Electric Vehicle for overcoming the range anxiety of the driver. The model accuracy is improved by considering the dynamic variations of solar radiation load during the trip. The result obtained from simulation is validated with real time data for the complete trip. The energy requirement of the vehicle before the journey, can be estimated through this model.