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.
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
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.
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.
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.
Smart Images

Figure CN116029140B_ABST