Comparative Analysis of Physical Temperature Sensing Technologies

The selection of a physical sensor for a battery pack involves balancing accuracy, cost, response time, and robustness to electromagnetic interference (EMI). While dozens of sensors may be embedded in a single automotive battery pack, the methodology of their placement and the technology chosen fundamentally limit the capability of the BMS.

Temperature gradients exist across a cell and between cells.

cell temperature gradient
Cells have a physical dimensions and inhomogeneous thermal conductivity, resulting in cell temperature gradients in the cell no matter where the cooling system interfaces with it.
Cell to Cell temperature gradients with exist due to the physical dimensions of the pack and the coolant extracting heat along it’s path.

However, battery packs are often made up of hundreds of cells and so it is unrealistic to have a physical sensor on every cell. Also, cells and packs have a thermal capacity that means in most general applications a well designed electro-thermal system will ensure quite uniform temperatures. High charge and discharge rates will be the challenging cases.

We must also consider the response if one or more temperature sensors fail as the impact of shutting the battery pack down could be just inconvenient or even safety critical.

Replacement of a temperature sensor with a part cost of a few pence versus the cost of downtime and service is incomparable.

Also, we need enough sensors that we can robustly check they are consistent.

Hence a full assessment must be made.

This post has been built based on the support of and sponsorship from: illumion, Custom Power, Quarto Technical Services, Eatron Technologies and About:Energy

Sensing Options

Conventional Contact Sensors: Thermistors, RTDs, and Thermocouples

Negative Temperature Coefficient (NTC) thermistors are the most prevalent solution in commercial battery packs due to their high sensitivity and low unit cost. Their resistance decreases exponentially with increasing temperature, providing high resolution within the typical operating range of a battery. However, their non-linearity necessitates complex look-up tables or high-order polynomial fits within the BMS firmware, and they are prone to significant resolution loss at temperatures exceeding 70°C.

Resistance Temperature Detectors (RTDs), typically based on platinum (Pt100 or Pt1000), provide a more linear and stable alternative. As the temperature of the metal element increases, the mobility of electrons decreases, causing a predictable rise in resistance. RTDs are favoured in laboratory settings and high-precision industrial applications because of their long-term stability and repeatability, though their higher cost and susceptibility to mechanical vibration limit their widespread use in automotive traction packs.

Thermocouples operate on the Seebeck effect, where the junction of two dissimilar metals generates a voltage proportional to the temperature gradient. While they offer the widest temperature range and are highly robust, the millivolt-level output is highly susceptible to EMI in the high-voltage environment of an electric vehicle. Furthermore, they require cold-junction compensation, adding complexity to the signal conditioning circuitry.

Advanced Optical and Fibre-Based Sensing

Fibre optic sensors represent a paradigm shift in battery monitoring. Fibre Bragg Grating (FBG) sensors use a tiny area inside an optical fibre that reflects specific wavelengths of light. As the fibre expands with temperature, the reflected wavelength shifts. Because these sensors are made of dielectric materials, they are entirely immune to EMI and can be placed in direct contact with high-voltage busbars or even embedded inside the cell.

Distributed Temperature Sensing (DTS) uses the entire length of an optical fibre as a sensor by analysing Raman backscattered light. This allows the BMS to monitor a continuous temperature profile along a long route, such as a cooling channel or a string of cells, rather than relying on discrete point measurements. The primary limitation of fibre optic systems is the initial cost of the interrogator and the limited bend radius of the fibre, which can make routing within compact modules challenging.

Conclusion

The selection of a physical temperature sensor needs to consider the temperature window, the robustness to electrical noise, accuracy, drift, physical size, reliability and cost (including any supporting electronics). We also need to understand the thermal system and what the temperature sensing needs to achieve and respond to.

Sensor FeatureNTC ThermistorRTD (Pt100)ThermocoupleFibre Optic (FBG)
CostVery LowModerateLowHigh
LinearityExponentialHighly LinearLinearLinear
Accuracy0.1°C to 1.5°C0.1°C to 1.0°C0.5°C to 2.0°C0.2°C to 1.0°C
EMI ImmunityLowLowVery LowTotal
ComplexitySimpleSimpleComplex (Comp.)High (Interrogator)
comparison of thermistor and thermocouple
Thermocouple vs Thermistor

The near linear response, robustness and wide operating temperature range make the thermocouple ideal for test environments. However, the need for more electronics and overall higher cost mean that the thermistor is better suited to the production environment.

References

  1. Pan, Y.; Xu, K.; Chen, Z.; Wang, K. Advanced Techniques for Internal Temperature Monitoring in Lithium-Ion Batteries: A Review of Recent Developments. Coatings 2025, 15, 268.
  2. Should You Choose an NTC Thermistor, Linear Thermistor or Analog Temperature Sensor? – Texas Instruments
  3. Comparing Thermocouples, Thermistors, & RTDs | Bench Talk, Mouser Electronics
  4. What’s the Difference Between Thermocouples and RTDs? – DwyerOmega
  5. COMPARISON OF FIBER OPTIC AND THERMOCOUPLE/RTD SENSORS – Advanced Energy
  6. Jinasena  A, Spitthoff  L, Wahl  MS, Lamb  JJ, Shearing  PR, Strømman  AH and Burheim  OS, Online Internal Temperature Sensors in Lithium-Ion Batteries: State-of-the-Art and Future Trends. Front. Chem. Eng.
  7. DTS vs FBG Fiber Optic Temperature Sensor: Key Differences Explained – Gato Security
  8. Jooste, Kritzman P., Almaktoof, Ali, Kahn, Mohamed T., Simulation-Based Approaches to Thermal Estimation in Electric Vehicle Battery Cells, Modelling and Simulation in Engineering, 2026, 3879940, 30 pages, 2026.

See also: Testing Equipment

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