EV Charge Management Server for Route-Based Battery Prediction

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Solution Overview

Problem

The accuracy of remaining battery capacity prediction in electric vehicles is low due to varying battery consumption based on environmental conditions, traffic, and load weight, causing inconvenience in using electric vehicles for transportation, especially when infrastructure for charging is insufficient.

Innovation Solution

A transportation management and battery charge management server that calculates driving routes and predicts remaining battery capacity by integrating regional and hourly data, road information, and real-time electric vehicle battery information, selecting optimal charging stations and adjusting routes based on predicted capacity and load changes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If electric vehicles are used for transportation purposes, then mobility and productivity are improved, but battery consumption varies due to environmental conditions, traffic, and load weight, causing low accuracy in remaining battery capacity prediction

Engineering Contradiction:

Improvetransportation capabilityVSAvoidremaining battery capacity prediction accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system performs preliminary action by predicting the remaining battery capacity before the vehicle reaches the destination. The server calculates estimated battery consumption based on the driving route, transportation time, and vehicle information in advance, allowing users to know the predicted remaining capacity before making charging decisions, thus resolving the accuracy issue of real-time monitoring alone

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system transitions from one-dimensional real-time battery monitoring to multi-dimensional prediction by incorporating driving route, transportation time, vehicle information, and historical battery consumption data. This dimensional expansion allows comprehensive consideration of environmental conditions, traffic, and load weight factors that affect battery consumption

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

2Loss of information

If real-time battery monitoring is provided, then user awareness of battery status is improved, but accuracy remains low due to varying consumption rates from environmental factors, traffic conditions, and load weight

Engineering Contradiction:

Improvebattery status information completenessVSAvoidbattery consumption accuracy

Core Design Contradiction:

Loss of informationVSMeasurement precision

Solution Approach 1:

The server acts as an intermediary between the vehicle's battery system and the user. It receives vehicle information including battery status, calculates driving routes and transportation times, predicts battery consumption, and provides comprehensive information to users. This intermediary processing resolves the accuracy problem by synthesizing multiple data sources rather than directly displaying raw battery data

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system replaces simple mechanical battery monitoring with an intelligent prediction system that uses servers, communication units, and processors. The server substitutes basic display mechanisms with sophisticated calculation and prediction algorithms that consider driving routes, transportation times, and historical data to provide accurate battery status information

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Reliability

If users individually search for charging stations, then charging needs can be met, but user convenience deteriorates due to the need to consider charging terminal specifications and charging time

Engineering Contradiction:

Improvecharging availabilityVSAvoidcharging station search convenience

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The server provides self-service by automatically calculating the driving route, predicting battery consumption, identifying suitable charging stations, and providing comprehensive charging information to users. Users simply need to input their destination, and the system handles all charging-related calculations and recommendations, eliminating the need for users to manually search and evaluate charging stations

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The server performs multiple functions: calculating driving routes, predicting battery consumption, selecting appropriate charging stations based on vehicle specifications, and providing charging time estimates. This multi-functionality resolves the convenience issue by consolidating all charging-related services into a single integrated system

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20240125607A1Transportation management and battery charge management server for transportation electric vehicle and controlling method thereof

Publication Date: 2024.04.18 KKUN

AI summary

A battery charge management server for an electric vehicle may include a storage unit configured to store and update transportation data, a communication unit configured to receive information on a destination and information on an electric vehicle battery from a user, and a processor configured to calculate a driving route and a transportation time to the destination based on the transportation data and the information on the destination, predict a remaining battery capacity of the electric vehicle battery after reaching the destination based on the driving route, the transportation time, and the electric vehicle battery, and providing the predicted remaining battery capacity.