EV Charge-Discharge Control Using Household Behavior Prediction
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Solution Overview
Problem
The fixed charge-discharge model for new energy vehicles is inflexible and cannot meet the varying needs of users, leading to insufficient power during urgent situations and potential battery life shortening due to over-charging or over-discharging.
Innovation Solution
A charge-discharge system that includes an electronic device capable of collecting user operation behavior information from household appliances, using a travel time prediction model to determine a dynamic charge-discharge strategy, and transmitting this strategy to a charging pile for implementation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed charge-discharge model is used, then the charging process is simple to control, but the system cannot adapt to varying user needs and may cause insufficient power or battery life shortening
Solution Approach 1:
The patent implements dynamic charge-discharge strategies that adjust charging parameters in real-time based on user behavior patterns, travel time predictions, and battery state. This transforms the static fixed charge-discharge model into a dynamic system that adapts to varying user needs while managing complexity through automated decision-making algorithms.
Solution Approach 2:
The system incorporates feedback mechanisms by monitoring user operation behavior information from household appliances, predicting travel times, and using this information to continuously optimize charge-discharge strategies. This closed-loop feedback enables the system to adapt to user needs while maintaining manageable complexity through data-driven decision making.
2Power
If fast charging is used to meet urgent power needs, then the vehicle power sufficiency is improved, but the battery life is significantly shortened due to over-charging
Solution Approach 1:
The system performs preliminary actions by analyzing user behavior patterns and predicting travel times in advance. This allows the system to proactively plan optimal charge-discharge strategies that ensure sufficient power availability before the user needs it, while avoiding excessive charging that would harm battery life. The prediction-based approach enables advance preparation without over-charging.
Solution Approach 2:
The patent dynamically adjusts charging parameters such as charging rate, power levels, and timing based on predicted travel times and user behavior patterns. By changing these parameters adaptively rather than using fixed fast charging, the system ensures sufficient vehicle power while optimizing battery life through controlled charging conditions.
3Duration of action of stationary object
If slow charging is used to extend battery life, then the battery durability is improved, but the vehicle power becomes insufficient for urgent situations
Solution Approach 1:
The system dynamically adjusts charging rates based on real-time predictions of user travel needs. When urgent power availability is predicted, the system increases charging rates appropriately; when extended battery life is the priority, it uses slower charging. This dynamic adjustment ensures both battery durability and adequate power availability for urgent situations.
Solution Approach 2:
The patent changes charging parameters adaptively based on predicted user behavior and travel time requirements. By adjusting power levels, charging rates, and timing parameters according to actual needs rather than using fixed slow charging, the system maintains battery durability while ensuring sufficient power availability when urgently required.
4Ease of operation
If a dynamic charge-discharge strategy based on user behavior prediction is implemented, then the system flexibility and user convenience are improved, but the system complexity and computational requirements increase
Solution Approach 1:
The system implements self-service by automatically analyzing user behavior patterns, predicting travel times, and determining optimal charge-discharge strategies without requiring direct user intervention. This automation improves user convenience while managing system complexity through integrated decision-making algorithms that operate autonomously based on collected data.
Solution Approach 2:
The patent uses feedback from monitoring user operation behavior information to continuously improve predictions and optimize charge-discharge strategies. This feedback-driven approach enhances user convenience through increasingly accurate predictions while managing system complexity through iterative learning and adaptation rather than requiring complex manual configuration.
Data Source
AI summary
A charge-discharge method applied to an electronic device for controlling a charging and a discharging of a vehicle, the electronic device communicates with a charging pile. The charge-discharge method comprises collecting operation behavior information of a user with respect to household appliances, inputting the operation behavior information into a preset travel time prediction model to obtain a first driving travel time of the user, determining a first charge-discharge strategy of the vehicle of the user based on the first driving travel time, and transmitting the first charge-discharge strategy to the charging pile. The charging pile charges the vehicle or controls the vehicle to discharge based on the first charge-discharge strategy. An electronic device and a non-transitory storage are also disclosed.