The problem
Electric two-wheelers often have no active cooling to keep cost and weight down, yet they run in very hot cities and ride in short, repeated trips. A PCM packed around the cells absorbs heat while melting and holds cell temperature near its melting point, but it only works if it can re-solidify between rides. This project quantifies whether PCM helps in Indian conditions and how much is needed.
Objectives
- Model PCM melting and solidification with the effective heat-capacity method.
- Build a lumped pack–PCM–housing thermal model with natural convection to ambient.
- Compare peak cell temperature with and without PCM over repeated ride–park cycles.
- Size PCM mass and melting temperature for a hot-climate duty cycle.
- Evaluate the recovery problem: whether the PCM re-solidifies between rides at high ambient.
What you need
Tools and toolboxes
- MATLAB — PCM property functions, parameter sweeps and design-space plots.
- Simulink — Lumped thermal model with integrators and lookup tables for effective heat capacity, drive-cycle current input and logging.
- Simscape — Optional: Thermal Mass and convection blocks for the non-PCM parts; the PCM node itself is clearer as a custom Simulink integrator with an enthalpy–temperature table.
Software
- MATLAB R2023b or later
- Simulink
- Simscape (optional)
- Excel/CSV for drive cycles
Extra parts and data
- Published PCM property data (melting range, latent heat, density, conductivity) — Paraffin-based PCM properties vary by grade, so the latent heat and melting range must come from a datasheet or paper for the chosen material.
Key concepts
- Latent heat
- Energy absorbed when a material melts at nearly constant temperature. Paraffin PCMs typically store well over a hundred kilojoules per kilogram as latent heat, much more than sensible heat over a few degrees.
- Effective heat-capacity method
- The latent heat is spread over a melting range as an extra heat capacity, so a single temperature equation handles solid, mushy and liquid states.
- Enthalpy method
- An alternative that integrates enthalpy and recovers temperature from an enthalpy–temperature table. It avoids numerical trouble when the melting range is narrow.
- Low thermal conductivity
- Paraffin conducts heat poorly, so heat may not reach all the PCM; composites with expanded graphite or metal foam improve conductivity.
Step-by-step guide
- 1
Define the pack and duty cycle
Use an example 60 V, 2 kWh scooter pack of cylindrical cells in a closed plastic housing. Define a duty cycle typical of city delivery work, for example 30 minutes of riding on IDC or a delivery profile followed by 15 minutes parked, repeated for several hours at 40 °C ambient. Set a requirement such as cell temperature below 45 °C. Record cell heat-generation parameters and housing natural-convection coefficient as example values.
Checkpoint: A parameter script and a duty-cycle timeseries spanning a full working shift.
- 2
Model heat generation and the base pack
Compute pack current from the speed profile with a simple vehicle model, and cell heat as I²R per cell. Build the no-PCM baseline with a pack thermal mass, a housing thermal mass and natural convection from housing to ambient. Use a variable-step solver and log temperatures with the Simulation Data Inspector. This baseline is the reference every PCM design is judged against, so keep its parameters fixed for the rest of the study.
Checkpoint: The baseline pack heats up through the shift and its peak temperature at 40 °C ambient is reported.
- 3
Implement the PCM model
Implement the PCM as an enthalpy integrator: dH/dt = Q_in − Q_out, with temperature recovered from H through a 1-D Lookup Table built from solid specific heat, latent heat spread over the melting range and liquid specific heat. Add a liquid fraction output. Test the PCM node alone with a constant heat input and check that temperature plateaus near the melting point for the expected time, latent heat times mass divided by heat input.
Checkpoint: The plateau duration matches m·L/Q within a few per cent, and liquid fraction rises from zero to one across it.
- 4
Couple cells, PCM and housing
Place the PCM node between cells and housing, linked by thermal resistances that reflect contact and the PCM's low conductivity. Include an effective conductivity parameter so a paraffin-only and a composite PCM can be compared. Check that with the PCM fully solid and no heat input, all nodes settle to ambient. Log heat flow from cells into the PCM and from PCM to housing separately to see where heat is stored and released.
Checkpoint: Equilibrium test passes and a single-ride test shows cell temperature rise slowed while the PCM melts.
- 5
Simulate the full shift
Run the repeated ride–park shift at 30, 35 and 40 °C ambient with and without PCM. Plot cell temperature and PCM liquid fraction against time. Look for the key effect: in the early rides the PCM holds temperature down, but if it cannot re-solidify during parking, it stays liquid and the pack behaves like a heavier no-PCM pack later in the shift.
Checkpoint: Plots showing liquid fraction across the shift and whether it returns towards zero during parking at each ambient.
- 6
Size mass and melting point
Sweep PCM mass and melting temperature, for example melting points from 35 to 45 °C. For each combination, record peak cell temperature over the shift and the final liquid fraction. Plot the design space and identify combinations that meet the requirement. Note that a melting point below the ambient temperature never re-solidifies, so it only helps for the first ride.
Checkpoint: A design-space plot with the feasible region and chosen design marked.
- 7
Compare conductivity enhancement
Repeat the best case with a composite PCM that has higher conductivity but lower latent heat per kilogram, using example properties from literature. Compare peak temperature, temperature spread and mass. Discuss the trade-off between storing more heat and moving heat faster. Keep total PCM volume fixed so the comparison is fair, and check the temperature difference between cells and PCM in each case, which shows whether heat transfer or storage capacity is the bottleneck.
Checkpoint: A comparison table for paraffin and composite PCM with the better choice justified.
- 8
Weight, cost and practical trade-offs
Compute added mass for each design and its effect on vehicle energy consumption using a simple road-load calculation. Discuss housing design, leakage of liquid PCM and fire behaviour of paraffin qualitatively. Compare with a small fan as an alternative and state which conditions favour each solution. Estimate the extra energy per kilometre from the added mass using the rolling-resistance and acceleration terms, and compare it with any benefit from running cells cooler.
Checkpoint: A trade-off table covering peak temperature, added mass and practical concerns for PCM and fan options.
- 9
Report
Present the PCM model and its verification, shift simulations, design-space results and trade-offs. State the limitations: lumped PCM ignores melt-front movement, natural convection in liquid PCM is ignored, and properties are from literature. Recommend a design or recommend against PCM if the recovery problem makes it ineffective at high ambient. Include the PCM verification test and the sweep scripts so the design space can be regenerated for another material.
Checkpoint: A report with a clear recommendation based on the shift simulations.
Testing & validation
- Plateau duration of the PCM node matches m·L/Q.
- Equilibrium and no-load tests pass.
- Peak temperature with and without PCM across ambient temperatures.
- Liquid fraction recovery during parking periods.
- Design-space sweep of mass and melting point.
Expected results
A lumped PCM pack model that shows when passive PCM cooling helps a two-wheeler in Indian city duty, with a sized design and a quantified view of the re-solidification problem at high ambient.
Research angle for your M.Tech thesis
Research questions: under what combinations of ambient temperature, ride–park pattern and melting point does passive PCM keep a two-wheeler pack within limits over a full working shift, and how does conductivity enhancement change that? Metrics: peak cell temperature, time above limit, end-of-shift liquid fraction and added mass. Baselines: natural air and a small fan. Validation: compare the lumped model with a 1-D conduction model and with published PCM pack experiments. Results specific to Indian urban duty cycles and high ambient, where re-solidification is the deciding factor, would be a useful contribution for a conference paper.
Take it further
- Build a 1-D or 2-D conduction model of the PCM to capture melt-front movement.
- Combine PCM with a small fan that runs only during parking to speed re-solidification.
- Couple to an electrical cell model so temperature affects resistance and capacity.
- Model fast charging between delivery rides.
Viva and review questions
Why must the melting point be above ambient?
The PCM can only re-solidify by losing heat to ambient, so if ambient is above the melting point it stays liquid and stops absorbing latent heat.
Why use the enthalpy method?
With a narrow melting range, the effective heat capacity becomes a sharp spike that is hard for solvers, while integrating enthalpy and looking up temperature stays smooth.
Why add expanded graphite to paraffin?
Paraffin conducts heat poorly, so heat cannot reach the PCM far from the cells; graphite raises conductivity, at the cost of some latent heat per kilogram.
Learn it at DIYguru
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