EV Battery Charging Location Prediction for Grid Load Management
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Solution Overview
Problem
The increasing demand for charging electric vehicles places a significant load on the electrical power grid, making it challenging to predict and manage the energy requirements and charging locations efficiently, leading to potential operational costs and grid capacity issues.
Innovation Solution
A method and control device that predict the charging location and required energy needs for a vehicle's next trip, transmitting this information to the power grid, allowing for optimized grid preparation and user-cost minimization by utilizing previous trip data, current location determination, and user input, while distinguishing between public and non-public charging locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If charging locations and energy requirements are predicted and transmitted to the power grid, then the power grid can prepare for anticipated energy loads and optimize charging times, but the system complexity and data processing requirements increase
Solution Approach 1:
The control device predicts charging locations and energy requirements before actual charging occurs, allowing the power grid to prepare in advance. This preliminary prediction action enables optimized charging schedules and load management, resolving the contradiction by performing data processing upfront rather than during charging operations.
Solution Approach 2:
The system transmits predicted charging data to the power grid, creating a feedback loop that enables the grid to adjust its operations. This feedback mechanism allows the grid to respond to predicted demands while the control device can refine predictions based on grid responses, managing system complexity through iterative improvement.
2Ease of operation
If the control device determines and registers charging locations (public or non-public), then charging accessibility and user convenience are improved, but the data management and processing requirements increase
Solution Approach 1:
The system segments charging locations into distinct categories (public charging locations and non-public charging locations). This segmentation simplifies data management by organizing locations into manageable groups with different access characteristics, reducing the overall data management burden while maintaining comprehensive charging accessibility information.
Data Source
AI summary
A method for charging a battery of a vehicle including at least one electric power train, the battery adapted to supply electrical energy to the electric power train, includes: predicting a charging location for charging the battery after at least one next trip of the vehicle; and transmitting the charging location to a power grid.