Battery early warning and monitoring system

• US 8,952,823 B2
• Filed: 01/20/2012
• Issued: 02/10/2015
• Est. Priority Date: 01/20/2011
• Status: Expired due to Fees

• Current Assignee: Indiana University Research & Technology Corporation (Indiana University)
• Original Assignee: Indiana University Research & Technology Corporation (Indiana University)
• Inventors: Xie, Jian, Chen, Jie
• Primary Examiner(s): Wang, Jack K
• Application Number:
  US13/355,320
• Publication Number:
  US 20120188086A1
• Time in Patent Office: 1,117 Days
• Field of Search: 340/636.18, 340/455, 324/433, 324/538
• US Class Current: 340/636.18
• CPC Class Codes: G01R 31/367 Software therefor, e.g. for battery testing using modelling or look-up tables
• CPC Class Codes: G01R 31/374 with means for correcting the measurement for temperature or ageing
• CPC Class Codes: G01R 31/382 Arrangements for monitoring battery or accumulator variables, e.g. SoC

Abstract

An early warning and monitoring system is disclosed for battery cells and battery packs. During normal cycling of a battery, surface temperature, voltage, current and impedance may be monitored to determine if abnormalities exist in the battery and/or battery structure. The abnormalities may be advantageously detected using battery temperature characteristics, where the characteristics are subject to rule-based processing to determine impending battery failure. By receiving advance notice of failure, a warning signal may be transmitted to provide notice and/or allow corrective action to be taken.

Claims

1. A method for monitoring a battery using a processor-based system, comprising the steps of:

receiving a temperature value measured from the battery in the system;

receiving a temperature differential value from the battery in the system;

receiving a state-of-charge (SoC) value measured from the battery in the system;

processing at least one of the (a) temperature value and (b) temperature differential value, together with the SoC value to determine if the battery is approaching a failure condition prior to an actual failure condition, the failure condition comprising a battery short resulting from one of an overcharge condition and an overdischarge condition; and

transmitting a warning signal if the processing step determined that a failure condition is approaching.

2. The method of claim 1, wherein the processing step comprises

loading a look-up table into the system and comparing the measured temperature differential value to one or more values in the look-up table,

wherein the look-up table comprises at least one of charge and discharge capacities over a plurality of different temperatures.

3. The method of claim 1, further comprising:

receiving an impedance value measured from the battery in the system and comparing the measured impedance value to one or more values in a look-up table, wherein the look-up table comprises at least one of charge and discharge capacities over a plurality of different temperatures.

4. The method of claim 1, wherein the processing step comprises loading a rule into the system, wherein the rule comprises predetermined temperature threshold values for a given voltage and a given current, and wherein an approaching battery failure condition is determined if the temperature value exceeds the predetermined temperature threshold value.

5. The method of claim 1, further comprising

receiving a voltage value measured from the battery in the system;

and

loading a rule into the system for the processing step, wherein the rule comprises predetermined voltage threshold values for a given voltage and a given current, and wherein an approaching battery failure condition is determined if the voltage value exceeds the predetermined voltage threshold value.

6. The method of claim 1, wherein the processing step comprises loading a temperature model into the system, and wherein an approaching battery failure condition is determined if the temperature value is outside one or more parameters of the temperature model.

7. The method of claim 6, wherein the temperature model is defined by Δ

T =T_S−

T_i=(q_chem +q_elec)R_tot, where T_S is the battery surface temperature, T_i is the battery internal temperature, q_chem is the heat flux due to ohmic heat, q_elec is the heat flux due to all other heat sources, and R_tot is the total thermal resistance of a cell.