In order to detect a cell voltage with high accuracy during an equalizing process among a plurality of cells, during execution of the equalizing process among the plurality of cells, controller measures a value of a current flowing to a negative electrode of an nth cell through an nth discharge resistor, calculates an (n−1)th voltage drop value due to a wiring resistance value of an (n−1)th wiring and an nth voltage drop value due to a wiring resistance value of an nth wiring based on the measured current value, and the wiring resistance value of the (n−1)th wiring connected to a positive electrode of the nth cell and a wiring resistance value of the nth wiring connected to the negative electrode of the nth cell, the wiring resistance value of the (n−1)th wiring and the wiring resistance value of the nth wiring being measured in advance, and, based on the (n−1)th voltage drop value and the nth voltage drop value, corrects the voltage value of the nth cell, a voltage value of an (n−1)th cell, and a voltage value of an (n+1)th cell measured by voltage measurement circuit.

The present invention relates to an electric battery (10). The electric battery (10) comprises plural battery cells (12), with each battery cell comprising a container. The container contains an electrochemical arrangement. Each battery cell (12) comprises positive and negative terminals of sheet form which extend from the electrochemical arrangement. The electric battery further comprises plural measurement arrangements (14), with each of the plural measurement arrangements being electrically coupled to each of two spaced apart locations on one of the positive and negative terminals of a respective one of the plural battery cells. Each of the plural measurement arrangements (14) is configured to measure potential difference between the two spaced apart locations.

The present invention relates to an electric battery (10). The electric battery (10) comprises plural battery cells (12), with each battery cell comprising a container. The container contains an electrochemical arrangement. Each battery cell (12) comprises positive and negative terminals of sheet form which extend from the electrochemical arrangement. The electric battery further comprises plural measurement arrangements (14), with each of the plural measurement arrangements being electrically coupled to each of two spaced apart locations on one of the positive and negative terminals of a respective one of the plural battery cells. Each of the plural measurement arrangements (14) is configured to measure potential difference between the two spaced apart locations.

A diagnostic device includes: a calculator that calculates a value related to a capacity of a battery cell based on a result of comparison between a measurement Q-V curve and a reference Q-V curve, the measurement Q-V curve indicating a relation between a voltage and an integrated current amount that are obtained from measurement data of the battery cell. The calculator further calculates at least one of: an amount of capacity deterioration caused by a voltage difference between the measurement Q-V curve and the reference Q-V curve by multiplying an inclination of the measurement Q-V curve by the voltage difference, and a temporary maximum capacity after capacity deterioration caused by a change in the inclination of the measurement Q-V curve to an inclination of the reference Q-V curve.

Provided is a battery degradation estimation device including a storage medium that stores computer-readable instructions, and a processor coupled to the storage medium, the processor executing the computer-readable instructions to: acquire time-series data including at least a voltage, SOC (State Of Charge), temperature, and current of a battery; convert the time-series data into intermediate data to be used for training; predict a future value of the intermediate data and a future value of an indicator relating to a degradation state of the battery by using a prediction function to generate training data; train a prediction model for estimating the indicator relating to the degradation state of the battery on the basis of the training data; and estimate the indicator relating to the degradation state of the battery on the basis of the prediction model.

The battery unit includes: a battery module including a battery cell; a battery heat flow detector configured to detect a heat flow of the battery cell; a storage configured to store heat flow HF vs. state of charge SOC initial characteristics of the battery cell; and a battery state estimator configured to estimate a state of health SOH of the battery cell. The battery state estimator measures, during charge of the battery cell, HF vs. SOC present characteristics of the battery cell, based on the detected heat flow of the battery cell, and estimates a state of health SOH of the battery cell, from a ratio between a length mAh of a line segment between peaks of differential characteristics of the measured HF vs. SOC present characteristics and a length mAh of a line segment between peaks of differential characteristics of the stored HF vs. SOC initial characteristics.

Disclosed is a method and a battery management system for calibrating a state of charge of a battery. The method includes measuring a terminal voltage and a current of the battery, storing a measured voltage value indicating the terminal voltage and a measured current value indicating the current in a memory, updating a state of charge of the battery based on the measured current value, estimating an open-circuit voltage of the battery based on a first number of measured voltage values and a first number of measured current values in the order stored in the memory, storing an estimated voltage value indicating the open-circuit voltage in the memory, and calibrating the updated state of charge with a reference state of charge when a calibration condition is satisfied by a data set in which a second number of estimated voltage values sequentially stored in the memory are arranged in sequential order.

Disclosed is a method and a battery management system for calibrating a state of charge of a battery. The method includes measuring a terminal voltage and a current of the battery, storing a measured voltage value indicating the terminal voltage and a measured current value indicating the current in a memory, updating a state of charge of the battery based on the measured current value, estimating an open-circuit voltage of the battery based on a first number of measured voltage values and a first number of measured current values in the order stored in the memory, storing an estimated voltage value indicating the open-circuit voltage in the memory, and calibrating the updated state of charge with a reference state of charge when a calibration condition is satisfied by a data set in which a second number of estimated voltage values sequentially stored in the memory are arranged in sequential order.

A state of charge of a battery is estimated by a battery model specific to the battery. The battery model provides a section-wise defined correlation of terminal voltage values depending on state of charge values. Each of sections of the battery model delimits a monotonic dependence of the correlation from others of the sections. By segmenting the correlation of terminal voltage values depending on a state of charge value into sections, each segment within such the section-wise defined correlation of terminal voltage values depending on state of charge values is mathematically spoken a bi-unique function suitable for transformation into an inverse function defined within the section. The estimated state of charge may be continuously refined by an iterative feedback loop including coulomb counting for estimating a battery charge value, where refined estimated battery charge values state of charge values at a previous cycle are projected forward to the current cycle.

A state of charge of a battery is estimated by a battery model specific to the battery. The battery model provides a section-wise defined correlation of terminal voltage values depending on state of charge values. Each of sections of the battery model delimits a monotonic dependence of the correlation from others of the sections. By segmenting the correlation of terminal voltage values depending on a state of charge value into sections, each segment within such the section-wise defined correlation of terminal voltage values depending on state of charge values is mathematically spoken a bi-unique function suitable for transformation into an inverse function defined within the section. The estimated state of charge may be continuously refined by an iterative feedback loop including coulomb counting for estimating a battery charge value, where refined estimated battery charge values state of charge values at a previous cycle are projected forward to the current cycle.