Ten-year forecast covering eight market sectors, including gas sensing, pressure sensing and moisture detection for electric vehicle and energy storage system applications. Remote monitoring and live control technologies included.

 

This report provides insight and market intelligence into the market for advanced battery pack sensors and remote monitoring of battery packs, including eight sensor types (hydrogen, carbon dioxide, volatile organic compound (VOC), pressure, moisture, humidity, aerosol and electrochemical impedance spectroscopy), as well as remote monitoring through gateway and wireless BMS (wBMS) approaches. The forecast covers a ten-year period from 2026-2036, and forms the most comprehensive market analysis to date on the integration of advanced sensors into battery packs in electric vehicles and energy storage systems. The role of regulation is also discussed in detail, regarding adoption of advanced sensor technologies.

 

Battery fires are a major concern for large battery pack deployments, especially in electric vehicles and energy storage systems. Thermal runaway is the cause of these fires. An initially high temperature or current causes a chain of exothermic reactions which further raise the temperature of cells within the pack until the batteries decompose, releasing more heat and debris and eventually causing fires. Conventional battery pack sensors monitor voltage, current, and temperature in order to predict and monitor thermal runaway within battery pack deployments. However, these sensors are not completely sufficient. For vehicles in park or delayed thermal runaway events caused by cell venting and later gas combustion, temperature sensors are unable to provide sufficiently early warning to prevent thermal runaway from leading to battery fires. Alternative sensor technologies are required.

 

During thermal runaway, reactions within the cells and evaporation of the electrolyte produce gases, which are vented into the pack. These gases also increase the pressure within the pack. Smoke and other particulate matter suspensions (aerosols) are also produced during thermal runaway, as components decompose.

 

This leads to several options for alternative sensors:

 

Of these sensor technologies, gas sensing is proving to be the most effective in providing early warning of thermal runaway, and will see widespread adoption by 2036.

Remote monitoring and control

Forecasts and market analysis

Key Aspects

•  Review of the history of sensor deployments in battery packs, especially temperature, voltage and current sensors
•  Breakdown of the stages of thermal runaway, including electrolyte decomposition and evaporation
•  Review of regulations around battery pack sensors

•  Benchmarking alternative sensors for conventional sensing streams (temperature, voltage and current), e.g. electrochemical impedance spectroscopy
•  Review of alternative sensing streams for detection of thermal runaway, including hydrogen, volatile organic compound and aerosol sensing
•  Analysis of other sensor applications, including sensors for monitoring battery component expansion (strain sensors) and sensors for detection of moisture and humidity in the battery pack

•  Player analysis, comparing sensor component providers and sensor package providers
•  Prediction of future trends in advanced sensor deployment
•  Market forecasts for eight sensor types from 2026-2036

•  Review of conventional wired systems and communications protocols (e.g. CAN-bus)
•  Analysis of methods for enabling remote communication including gateways and wireless communications protocols
•  Player analysis and general prediction of remote monitoring trends

1.1. The scope of this report

1.2. Who should read this report?

1.3. Research methodology

1.4. Conventional battery sensors

1.5. Advanced sensors and alternatives

1.6. Regulatory background: Electric vehicles

1.7. The need for further regulation

1.8. Sensor technology benchmarking

1.9. Problems solved by advanced sensor deployments

1.10. Comparing gas sensing technologies

1.11. Comparing pressure sensor technologies

1.12. Comparing strain sensor technologies

1.13. Player analysis: Individual sensors vs complete package

1.14. Sensor type benchmarking

1.15. Remote monitoring and control

1.16. Comparing remote monitoring methods

1.17. Interest by region

1.18. Scope of forecasts

1.19. Methodologies

1.20. Advanced battery sensors units sold forecast

1.21. Advanced battery sensors market value forecast

1.22. Advanced sensor market 2036 by broad market sector

1.23. Advanced battery sensor market sector analysis

1.24. Advanced battery sensor market sector analysis cont.

1.25. Remote monitoring conclusions

1.26. Access More With an IDTechEx Subscription

 

2.1. The battery management system

2.2. Generic BMS block diagram

2.3. BMS topologies

2.4. BMS core functionality

2.5. Functions of a BMS

2.6. Cell control

2.7. BMS components

2.8. Battery pack structure

2.9. Thermal runaway

2.10. Cell venting events

2.11. Battery degradation

2.12. Applications: EVs and BESS

2.13. Need to improve

2.14. Avenues for improvement

2.15. Advanced analytics via alternative sensors

 

3.1. BMS targets: SoC, SoH and temperature

3.1.1. Conventional temperature sensors

3.1.2. Temperature sensors

3.1.3. Accuracy, range and response time requirements for temperature sensors in battery packs

3.1.4. Thermocouples

3.1.5. Thermistors

3.1.6. Resistance temperature detectors

 

3.2. Alternative temperature sensors

3.2.1. Optical fibre sensors: Point sensors and spectral shift

3.2.2. Optical fibre sensors: Design

3.2.3. Optical fibre sensors: Fibre Bragg gratings (FBGs)

3.2.4. Optical fibre sensors: Fabry-Pérot interferometers (FPIs)

3.2.5. Johnson noise thermometry

3.2.6. Infrared temperature sensors

3.2.7. Comparing temperature sensor technologies

3.2.8. Temperature sensor conclusions

 

3.3. Voltage and current sensors: Conventional technologies

3.3.1. Current and voltage measurements: The current shunt

3.3.2. Hall sensors and magneto-resistance sensors

3.3.3. SoC calculation: Coulomb counting

3.3.4. SoC calculation: Voltage look-up

3.3.5. SoH estimation

 

3.4. Alternative electrochemical state estimation methods

3.4.1. Advancements in SoH measurement: Electrochemical impedance spectroscopy (EIS)

3.4.2. How EIS is used

3.4.3. Advantages of EIS

3.4.4. Necessary modifications to the battery pack

3.4.5. Module- vs cell-level EIS

3.4.6. Marelli

3.4.7. CSEM

3.4.8. Conclusions on integration of EIS into battery packs

 

4.1.1. The need for new approaches

4.1.2. Advantages of low-power sensor deployments

4.1.3. State changes during thermal runaway

4.1.4. The process of battery component degradation during thermal runaway

4.1.5. Cell venting

4.1.6. Gas emission

4.1.7. Gas emission by cathode type

4.1.8. Gas emission vs. state of charge (SoC)

4.1.9. Gas sensor requirements

4.1.10. Cross-sensitivities in gas sensing

4.1.11. Pressure sensing - the basics

4.1.12. Pressure trends during thermal runaway

 

4.2. Hydrogen emission detectors

4.2.1. Hydrogen emission

4.2.2. Post-runaway combustion events

4.2.3. Principles of thermal conductivity sensing

4.2.4. Thermal conductivity sensor designs

4.2.5. Challenges of thermal conductivity sensing

4.2.6. Amphenol Advanced Sensors: Hydrogen

4.2.7. Posifa Technologies: Hydrogen

4.2.8. Chemi-resistive sensing

4.2.9. Selectivity vs sensitivity

4.2.10. Hydrogen sensing through chemi-resistive sensors

4.2.11. Nexceris

 

4.3. Volatile organic compound detectors

4.3.1. Volatile organic compounds: An introduction

4.3.2. Emission during runaway

4.3.3. Photoionization detector principle

4.3.4. Photoionization detectors

4.3.5. Metal oxide chemi-resistors

4.3.6. Li-ion Tamer ®

 

4.4. Carbon dioxide emission detectors

4.4.1. Carbon dioxide as a thermal runaway product

4.4.2. Non-dispersive infrared spectrometry (NDIR spectrometry)

4.4.3. NDIR CO2 sensor designs

4.4.4. Chemi-resistive carbon dioxide sensors

 

4.5. Carbon monoxide emission detectors

4.5.1. Carbon monoxide emission from thermal runaway

4.5.2. Tunable diode laser spectroscopy (TDLS)

4.5.3. Electrochemical sensors

4.5.4. Chemi-resistive sensors for carbon monoxide

4.5.5. Comparing gas sensing technologies

4.5.6. Gas sensor conclusions

4.5.7. Aerosol detectors

4.5.8. Aerosols present in the battery pack

4.5.9. Detection via light scattering

4.5.10. Honeywell

4.5.11. Sensing via ionization detectors

4.5.12. Pressure sensors

4.5.13. Pressure build-up during runaway

4.5.14. Typical pressure in a battery pack

4.5.15. Capacitive sensors

4.5.16. Piezoelectric sensors

4.5.17. Piezoresistive sensors

4.5.18. Infineon

4.5.19. Comparing pressure sensor technologies

 

5.1.1. Battery volume changes

5.1.2. Electrode expansion by material for lithium-ion batteries

5.1.3. Silicon anode batteries

5.1.4. Correlating degradation with trends in volume changes

5.1.5. Dendrite detection: differential pressure

 

5.2. Stress/strain detectors

5.2.1. Stress and strain

5.2.2. Benefits of stress/strain detection

5.2.3. Typical pressure in a battery pack

5.2.4. Strain gauges

5.2.5. Foil vs silicon

5.2.6. Thin-film strain gauges

5.2.7. Optical fibre sensors: Bragg gratings

5.2.8. Optical fibre sensors: Distributed sensors

5.2.9. Comparing strain sensor technologies

5.2.10. Stress/strain sensor conclusions

 

6.1. Moisture presence in the battery pack enclosure

6.2. Coolant leakage causes

6.3. Moisture detection via resistance

6.4. Moisture sensor design

6.5. Amphenol Advanced Sensors: Moisture detection

6.6. Humidity and dew points

6.7. Humidity control during battery manufacturing

6.8. The importance of dewpoints in a battery pack

6.9. Relative humidity detection

6.10. Absolute humidity detection

6.11. Metis Engineering

 

7.1. Communication protocols in battery packs

7.2. Important factors in battery pack sensor communication

7.3. Wired vs wireless

7.4. Benefits of remote monitoring

7.5. Proprietary vs standardized

7.6. Controller area network (CAN) protocol

7.7. Advantages of CAN

7.8. RS-485

7.9. Universal asynchronous receiver/transmitter (UART)

7.10. Remote monitoring through wired conversion

7.11. Ethernet

7.12. Wireless options

7.13. Bluetooth Low Energy (BLE)

7.14. Zigbee

7.15. Near-field communications (NFC)

7.16. Wi-fi and cellular networks

7.17. Menred ESS

7.18. MOKOENERGY

7.19. Nuvation Engineering

7.20. GM Motors

7.21. Comparing remote monitoring methods

7.22. Conclusions on remote monitoring BMSs

 

8.1. Advanced battery sensors units sold forecast

8.2. Advanced battery sensors market value forecast

8.3. Remote monitoring conclusions

 

9.1. List of company profile links