US-12620634-B2 - Predictive thermal models for current and power capability estimation

US12620634B2US 12620634 B2US12620634 B2US 12620634B2US-12620634-B2

Abstract

Methods and systems are provided for predictive thermal models for determining current and power capabilities of battery components of a battery-powered system. In one example, a method may include measuring a reference temperature of a first component of the battery-powered system, correlating a target temperature of a second component of the battery-powered system to the reference temperature, determining a maximum current manageable by the second component over a predetermined duration based on the target temperature, and responsive to an actual current at the second component being requested greater than the maximum current during the predetermined duration, adjusting one or more operating conditions of the battery-powered system to maintain the actual current below the maximum current. In some examples, the first component may be different from the second component. In this way, the methods and systems provided herein may mitigate overheating in a battery-powered system by altering an operating state thereof.

Inventors

Wei Zhao
Yufeng Liu
Shawn Zhang

Assignees

A123 SYSTEMS LLC

Dates

Publication Date: 20260505
Application Date: 20210604

Claims (8)

1 . A battery management system of a battery system, comprising: a temperature sensor; a current detection circuit; and a driver integrated circuit communicably coupled to each of the temperature sensor and the current detection circuit, the driver integrated circuit comprising a logic subsystem and a memory, the memory storing computer readable instructions executable by the logic subsystem to: measure one or more currents using the current detection circuit; measure a reference temperature of a first component of the battery system using the temperature sensor; predict a target temperature of a second component of the battery system based on the reference temperature, a calibratable gain factor, and the one or more measured currents; determine based on the predicted target temperature of the second component, an electrical resistance of the second component, and a thermal resistance between the second component and an ambient environment, each of a maximum current manageable by the second component and a maximum power manageable by the second component; and automatically adjust operating conditions of the battery system to respectively reduce an actual current or an actual power of the second component and concomitantly reduce a temperature of the second component in response to a request for current surpassing the determined maximum current over a time pulse duration and/or a request for power surpassing the determined maximum power over the time pulse duration, wherein the reference temperature of the first component is measured at a position that does not spatially overlap with a position of the second component, and wherein the requested current or the requested power is determined for the second component.
2 . The battery management system of claim 1 , wherein each of the one or more measured currents is measured at a separate time step prior to or at a beginning of the time pulse duration, and wherein predicting the target temperature of the second component based on the reference temperature and the one or more measured currents comprises: determining an effective current passing through the second component by weighting the one or more measured currents; and predicting the target temperature of the second component based on the reference temperature and the effective current.
3 . The battery management system of claim 1 , further comprising a voltage detection circuit communicably coupled to the driver integrated circuit, wherein the computer readable instructions are further executable to measure a voltage using the voltage detection circuit, and wherein determining each of the maximum current and the maximum power comprises: determining the maximum current based on the target temperature; and determining the maximum power based on the maximum current, the one or more measured currents, and the voltage.
4 . The battery management system of claim 1 , wherein determining each of the maximum current and the maximum power is continuously performed at a predetermined frequency while the battery management system is switched ON.
5 . The battery management system of claim 1 , wherein the second component is inaccessible for placement of the temperature sensor.
6 . A battery management system of a battery system, comprising: a temperature sensor; a current detection circuit; and a driver integrated circuit communicably coupled to each of the temperature sensor and the current detection circuit, the driver integrated circuit comprising a logic subsystem and a memory, the memory storing computer readable instructions executable by the logic subsystem to: measure a reference temperature of a first component of the battery system using the temperature sensor; measure a measured current at a second component of the battery system using the current detection circuit, wherein the second component is not accessible for placement of a temperature sensor; determine an effective current at the second component based on the measured current, wherein the effective current is a filtered current determined via a low-pass filter for a time following when the measured current is measured; estimate a target temperature of the second component based on the reference temperature of the first component and the effective current of the second component; using the target temperature, an electrical resistance of the second component, and a thermal resistance between the second component and an ambient environment, determine a maximum current and/or maximum power manageable by the second component over a predetermined duration to maintain the second component below a maximum temperature; and automatically adjust operating conditions of the battery system in response a request for current to the second component surpassing the maximum current to maintain an actual current at the second component below the maximum current and concomitantly reduce a temperature of the second component in response to a request for current surpassing the determined maximum current over a time pulse duration and or a request for power surpassing the determined maximum power over the time pulse duration.
7 . The battery management system of claim 6 , wherein the effective current is a filtered current determined via a low-pass filter for a time following when the measured current is measured.
8 . A battery management system of a battery system, comprising: a temperature sensor coupled to a first component; a current detection circuit; and a driver integrated circuit communicably coupled to each of the temperature sensor and the current detection circuit, the driver integrated circuit comprising a logic subsystem and a memory, the memory storing computer readable instructions executable by the logic subsystem to: estimate a target temperature of a second component of the battery system based on a temperature of the first component measured by the temperature sensor; based on the target temperature, an electrical resistance of the second component, and a thermal resistance between the second component and an ambient environment, determine a maximum current and/or maximum power manageable by the second component over a predetermined duration to maintain the second component below a maximum temperature; and automatically adjust operating conditions of the battery system in response a request for current to the second component surpassing the maximum current to maintain an actual current at the second component below the maximum current and concomitantly reduce a temperature of the second component in response to a request for current surpassing the determined maximum current over a time pulse duration and or a request for power surpassing the determined maximum power over the time pulse duration.

Description

CROSS REFERENCE TO RELATED APPLICATIONS The present application claims priority to U.S. Provisional Application No. 63/036,916, entitled “PREDICTIVE THERMAL MODELS FOR CURRENT AND POWER CAPABILITY ESTIMATION,” and filed on Jun. 9, 2020. The entire contents of the above-identified application are hereby incorporated by reference for all purposes. FIELD The present description relates generally to predictive thermal models, particularly for determining current and power capabilities in a battery system including a secondary battery cell. BACKGROUND AND SUMMARY Lithium-ion battery packs are increasingly sought after for high-power applications, such as electric, plug-in hybrid-electric, and mild hybrid-electric vehicles. In such battery systems, high currents may pass through various electrical and electronics components therein due to high power demands from the vehicle. In some examples, such high currents may result in overheating and degradation of one or more of the electrical and electronics components. Accordingly, accurate current and power capability estimation is desirable in high-power battery systems. Monitoring dynamic temperature fluctuations in battery systems may permit such accurate estimation of current and power capabilities. Temperature monitoring may be realized via one or more temperature sensors placed in locations having a large enough surface area for a given temperature sensor, having particular criticality to battery operation, and where the given temperature sensor may be unlikely to be damaged. As a first example, the temperature sensor may be placed on a body of a battery cell to monitor a cell temperature. However, overheating may occur in other portions of the battery cell which may be less accessible for placement of the temperature sensor, such as an electrode tab of the battery cell. For instance, in a lithium-ion pouch cell, high current may result in an electrode tab of the lithium-ion pouch cell being heated faster in than a body of the lithium-ion pouch cell. In some examples, such electrode tab overheating may result in reduced functionality of the lithium-ion pouch cell. As one example, an overheated electrode tab may melt a pouch casing of the lithium-ion pouch cell, potentially resulting in electrolyte leakage. As a second example, the temperature sensor may be placed on a surface of a printed circuit board (PCB) to monitor a temperature of a battery management system (BMS). However, power electronics components on the PCB, such as metal-oxide-semiconductor field-effect transistor (MOSFET) and relay switches, may be less accessible for placement of the temperature sensor. Heating of (unmonitored) individual power electronics components may outpace heating of the (monitored) PCB surface, resulting in faster degradation of the individual power electronics components relative to the PCB surface. To account for differences in temperatures and heating rates, a measured temperature at a monitored physical location may be correlated with an unmeasured temperature at an unmonitored physical location. For example, a complex thermal diffusion model may be implemented in a BMS of a battery system to estimate an internal temperature of a battery component based on a measured external temperature thereof. The inventors herein have recognized potential issues with such models. As one example, BMS controllers, on which the thermal diffusion models may be implemented, may be limited in computational and memory resources. The algorithms known in the art to accurately model internal temperatures in battery systems are computationally taxing and utilize many empirical parameters, each of which may first be fit to experimental data tailored to a given application. Extensive testing may therefore be a prerequisite before acquisition of accurate results is possible. Further, algorithms for modeling of internal temperatures may not be generalizable to determining temperatures of arbitrary components in the battery system. Specifically, such algorithms may assume thermal conduction is the sole mechanism of heat transfer (as may be the case between an external cell body and a cell interior, for example). However, for some thermally connected pairs of battery components, other factors may influence heat transfer therebetween. A generalized algorithm may account for such factors by including as inputs thermal properties of a given pair of battery components, such as thermal conductivity and thermal capacitance. However, though such properties may be relatively easy to measure for some battery components, such as a battery cell body, for other components, such as electrode tabs, there may be significant difficulty in obtaining accurate measurements. Additionally, once such unmeasured temperatures have been estimated, no method exists for determining current and power capabilities therefrom and then adjusting battery operation accordingly. Accordingly, a determination of overheating at a given ba