Battery Charging Plan Using Predicted SOC Distribution

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Solution Overview

Problem

Existing methods for creating charging plans for secondary batteries in businesses like taxi and rental car services are ineffective due to difficulty in predicting external variables such as travel distance and start time, making it challenging to optimize charging and traveling conditions to suppress battery degradation.

Innovation Solution

A charging plan creation system that uses statistical processing of battery pack use histories to create a predicted distribution of use amounts per day, allowing for the determination of optimal charging end State Of Charge (SOC) distributions for battery packs, thereby optimizing charging plans to reduce battery degradation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If statistical processing of use histories is performed to create predicted distribution, then charging plan optimization is achieved, but system complexity increases

Engineering Contradiction:

Improvecharging plan optimization efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system performs statistical processing on historical use data in advance to build predicted distribution models and charging plan templates. By pre-calculating optimal charging strategies based on historical patterns, the system reduces real-time computational complexity while maintaining optimization effectiveness.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates predicted distribution copies from actual use history data, generating statistical models that replicate real-world usage patterns. These copied distributions serve as the basis for optimization without requiring complex real-time analysis of actual operational data.

Inventive Principle:

Principle #26Copying

2Reliability

If charging end SOC distribution is determined based on predicted use amounts, then battery degradation is suppressed, but measurement and prediction accuracy requirements increase

Engineering Contradiction:

Improvebattery degradation suppressionVSAvoiduse amount prediction accuracy

Core Design Contradiction:

ReliabilityVSMeasurement precision

Solution Approach 1:

The system segments the battery fleet into groups with similar usage patterns and determines charging end SOC distributions for each segment separately. This segmentation approach reduces the precision requirements for individual battery predictions while maintaining overall degradation suppression effectiveness through group-level optimization.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system transforms individual battery prediction requirements into aggregate distribution parameters. Instead of requiring precise prediction for each battery, the system works with statistical distribution parameters (mean, variance) that are more robust to measurement errors and easier to estimate from historical data.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20250033516A1Charging plan creation system, charging plan creation method, and non-transitory computer-readable recording medium

Publication Date: 2025.01.30 PANASONIC INTELLECTUAL PROPERTY MANAGEMENT CO LTD

AI summary

A predicted distribution creation unit performs statistical processing on use histories of a plurality of battery packs used by being mounted on a moving body and creates a predicted distribution of the use amounts of the plurality of battery packs per day. A charging plan creation unit creates charging plans of the plurality of battery packs prepared for the operation of a target date on the basis of the created predicted distribution of the use amounts of the plurality of battery packs. The charging plan creation unit determines the distribution of charging end SOCs (State Of Charge) of the plurality of battery packs on the basis of the predicted distribution of the use amounts.