A short-term charging load prediction model of electric vehicles considering temperature influence

By combining the energy flow model of electric vehicles and the longitudinal dynamics balance equation of vehicles, and taking into account the effects of temperature and user behavior, a short-term charging load prediction model for electric vehicles is established. This solves the problem of randomness and uncertainty in electric vehicle charging behavior, and achieves more accurate load prediction and grid-friendly interaction.

CN116029140BActive Publication Date: 2026-07-21SUQIAN WANDA POWER IND CO LTD +3
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
SUQIAN WANDA POWER IND CO LTD
Filing Date
2023-01-13
Publication Date
2026-07-21

AI Technical Summary

Technical Problem

Electric vehicle charging behavior is affected by factors such as temperature and user habits, resulting in randomness and uncertainty in charging and discharging behavior. Existing models are unable to accurately predict short-term charging load, which affects power grid planning and control.

Method used

A short-term charging load prediction model for electric vehicles that takes into account the temperature effect is established. Combining the energy flow model of electric vehicles and the longitudinal dynamic balance equation of the vehicle, the influence of air conditioning power consumption is fitted by statistical data and maximum likelihood estimation. Considering the auxiliary load of the battery thermal management system, the prediction model is established using Monte Carlo sampling method and probabilistic charging method.

Benefits of technology

It improves the accuracy of short-term charging load forecasting for electric vehicles, reflects the distribution pattern of charging load under different temperatures, provides a reference for friendly interaction between the power grid and electric vehicles, and makes full use of the flexibility of charging demand and discharge potential.

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Abstract

The present application relates to a kind of short-term charging load prediction model of electric vehicle considering temperature influence, comprising the following steps: step 1: establishing electric vehicle driving power consumption model;Step 2: fitting distribution to the opening duration of air conditioner under different temperature intervals, different types of electric vehicle user single trip, calculate the mileage reduction rate of electric vehicle;Step 3: combined with vehicle accessory power consumption model, calculate the whole vehicle power consumption model;Step 4: based on Monte Carlo sampling method and probability charging method, establish the short-term charging load prediction model of electric vehicle.The present application uses maximum likelihood estimation method to fit the distribution of processed data, establishes the whole vehicle power consumption model per mile considering temperature influence, is conducive to accurately analyzing the charging demand of electric vehicle under different temperatures, provides reference value for solving how to make full use of the flexibility of electric vehicle charging demand and the potential of discharging to power grid.
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