# US 11,906,594 B2 · Method for estimating internal resistance of secondary battery and anomaly detection system of secondary battery

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- Number: US 11,906,594 B2
- Document ID: US11906594B2
- Status: Granted
- Kind: B2
- Application number: 17/612,323
- Filed: 2020-05-15
- Published: 2022-08-18
- Granted: 2024-02-20
- Earliest claimed: 2019-05-24
- Assignees: Semiconductor Energy Laboratory Co., Ltd.
- Applicants: Semiconductor Energy Laboratory Co., Ltd.
- Inventors: Jo Saito; Mayumi Mikami
- Web page: https://patentgrep.com/patent/US11906594B2

## CPC

- G01R 31/389: Measuring internal impedance, internal conductance or related variables
- B60L 3/0046: {relating to electric energy storage systems, e.g. batteries or capacitors}
- B60L 7/10: Dynamic electric regenerative braking (B60L7/22 takes precedence)
- B60L 7/18: Controlling the braking effect (B60L7/12, B60L7/14, B60L7/16 take precedence)
- B60L 58/12: responding to state of charge [SoC]
- B60L 58/15: Preventing overcharging
- B60L 58/16: responding to battery ageing, e.g. to the number of charging cycles or the state of health [SoH]
- G01R 31/367: Software therefor, e.g. for battery testing using modelling or look-up tables
- G01R 31/382: Arrangements for monitoring battery or accumulator variables, e.g. SoC
- G01R 31/392: Determining battery ageing or deterioration, e.g. state of health
- H01M 10/44: Methods for charging or discharging (circuits for charging H02J7/00)
- H01M 10/48: Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte (constructional details of current conducting connections for detecting conditions inside cells or batteries, e.g. details of voltage sensing terminals, H01M50/569)
- H02J 7/00: Circuit arrangements for charging or discharging batteries or for supplying loads from batteries
- B60L 2240/545: Temperature
- B60L 2240/547: Voltage
- B60L 2240/549: Current
- B60L 2250/16: by display
- B60L 2260/46: by self learning
- B60L 2260/50: by future state prediction
- Y02E 60/10: Energy storage using batteries
- G01R: MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES (indicating correct tuning of resonant circuits H03J3/12)
- B60L: PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES (arrangements or mounting of electrical propulsion units or of plural diverse prime-movers for mutual or common propulsion in vehicles B60K1/00, B60K6/20; arrangements or mounting of electrical gearing in vehicles B60K17/12, B60K17/14; preventing wheel slip by reducing power in rail vehicles B61C15/08; dynamo-electric machines H02K; control or regulation of electric motors H02P); SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES (electric coupling devices combined with mechanical couplings of vehicles B60D1/64; electric heating for vehicles B60H1/00); ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL (control or regulation of electric motors H02P); MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- H01M: PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H02J: ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- Y02E: REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION

## Abstract

An electric automobile incorporating a secondary battery has a disadvantage such as a difficulty in knowing the remaining capacity accurately and in predicting the time when the remaining capacity becomes zero because of deterioration of the secondary battery. The internal resistance is estimated with high accuracy even when the secondary battery deteriorates. Data used for learning or estimation is a data group (also referred to as data with regenerative charging) that is limited to data acquired within a certain time range around the end of regenerative charging. Such data within the limited range is extracted, used for learning, and subjected to the estimation. Thus, a value of the internal resistance can be output with high accuracy, specifically, with a mean error rate of 1% or less.

## Claims

### Claim 1

A method for estimating internal resistance of a secondary battery in an electric vehicle,
wherein a vehicle comprises a secondary battery, a learned neural network portion for estimating internal resistance of the secondary battery, a regenerative brake for performing regenerative charging on the secondary battery, and a charging circuit for the regenerative charging of the secondary battery,
wherein the method comprises:
performing regenerative charging of the secondary battery when a brake of the vehicle runs;
measuring data of the secondary battery while the electric vehicle is stopped with regenerative charging not running;
inputting the data of the secondary battery to the learned neural network portion; and
outputting estimated internal resistance of the secondary battery from the learned neural network portion, and
wherein the data of the secondary battery is data limited within a first time range around an end of the regenerative charging.

### Claim 2 (depends on 1)

The method for estimating internal resistance of a secondary battery in an vehicle according to claim 1, wherein the first time range comprises a point of time before the end of regenerative charging and a point of resting time later than the end of regenerative charging.

### Claim 3 (depends on 1)

The method for estimating internal resistance of a secondary battery in an vehicle according to claim 1, wherein each of learning data to prepare the learned neural network portion and the data of the secondary battery includes one or more selected from a temperature, a voltage, a power, a current and a voltage.

### Claim 4

A method for detecting an anomaly of a secondary battery in an electric vehicle,
wherein a vehicle comprises a secondary battery, a learned neural network portion for estimating internal resistance of the secondary battery, a regenerative brake for performing regenerative charging on the secondary battery, and a charging circuit for the regenerative charging of the secondary battery,
wherein the method comprises:
performing regenerative charging of the secondary battery when a brake of the vehicle runs;
measuring data of the secondary battery while the electric vehicle is stopped with regenerative charging not running;
inputting the data of the secondary battery to the learned neural network portion;
outputting estimated internal resistance of the secondary battery from the learned neural network portion; and
comparing a value of the estimated internal resistance with a reference value stored in advance as a range of a normal internal resistance in a memory.