Charging Station Selection Using SOC Range and User Preferences
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Solution Overview
Problem
The insufficient spread of charging stations for electric vehicles leads to long waiting times for users, as multiple users may need to share a single charger, hindering convenient battery charging.
Innovation Solution
A method using a battery scheduling device to determine a charging station based on user preferences and available charging stations within a movable range, considering factors like charging cost, availability, performance, and travel distance, utilizing a neural network for personalized recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the number of charging stations is increased to reduce waiting time, then user convenience is improved, but infrastructure cost and complexity increase
Solution Approach 1:
The patent introduces a charging station determination device as an intermediary system that coordinates between multiple charging stations and electric vehicles. This device receives charging requests, determines optimal charging stations based on various parameters (SOC, movement range, user preferences), and manages charging reservations. By centralizing the coordination function, the system reduces waiting time without requiring proportional increases in charging station infrastructure.
Solution Approach 2:
The system performs preliminary determination of charging stations before users actually need to charge. By proactively identifying suitable charging stations based on current vehicle state and user preferences, and allowing advance reservations, the system prepares charging resources in advance. This preliminary action reduces actual waiting time at charging stations without requiring additional infrastructure.
2Ease of operation
If charging stations are distributed more widely to improve accessibility, then user convenience is improved, but infrastructure cost increases
Solution Approach 1:
The system dynamically evaluates multiple parameters including state of charge (SOC), movement range, user preferences, and charging station availability to determine optimal charging stations. By changing the decision-making parameters from simple geographic proximity to a multi-factor evaluation system, the patent improves charging accessibility without requiring uniform geographic distribution of charging stations. The system can adapt to varying conditions and select from existing infrastructure based on real-time parameters.
Solution Approach 2:
The charging station determination device serves multiple functions: it identifies charging stations, evaluates their suitability based on various parameters, manages reservations, and provides recommendations to users. This multi-functional approach allows the system to improve charging accessibility across different locations and conditions without requiring dedicated infrastructure for each function, thereby reducing overall infrastructure complexity.
3Productivity
If multiple users share limited charging stations, then infrastructure utilization is improved, but waiting time increases
Solution Approach 1:
The system continuously monitors charging station status, user preferences, and vehicle states, using this feedback to dynamically determine optimal charging station assignments. By implementing feedback loops that track charging completion, availability, and user satisfaction, the system can optimize utilization while minimizing waiting times through intelligent redistribution of charging requests to appropriate stations based on real-time conditions.
Solution Approach 2:
The charging station determination system dynamically adjusts charging station recommendations and reservations based on changing conditions such as vehicle state of charge, user preferences, charging station availability, and traffic conditions. This dynamic approach allows the system to optimize both utilization and waiting time by adapting to real-time changes rather than using static allocation, enabling better coordination of multiple users across the charging network.
Data Source
AI summary
Disclosed according to some embodiments of the present disclosure is a method for determining a charging station, which is performed by a battery scheduling device that performs scheduling for battery operation of a moving object. The method for determining a charging station may comprise the steps of: when a specific condition is satisfied, determining, on the basis of a current location of the moving object and a state of charge (SOC) of the battery, a movement range indicating a range in which the moving object can move from the current location; determining at least one charging station present within the movement range; and determining a first charging station among the at least one charging station on the basis of predetermined preference information of a user and information related to the at least one charging station.