MSc Coursework · 2026
Electric Vehicle Simulation
A MATLAB/Simulink study of electric power demand, battery energy use and range across two driving cycles, with a comparison of regenerative braking settings.
Project at a Glance
- Approach
- Two driving cycles compared at regeneration coefficients of 0.25 and 0.65.
- Key Finding
- The report shows a 5.08% range increase for Cycle 1; Cycle 2 shows no reported change.
- Tools
- MATLAB · Simulink · Energy and range calculations
- Evidence
- Coursework report, model screenshot and reported simulation figures; model runs not independently reproduced.
Objective
Compare the power demand, energy consumption and simulated range of an electric vehicle under two driving cycles, then examine how increasing the regeneration coefficient changes the results.
Model and My Contribution
I updated the supplied coursework model with a vehicle mass of 1,956.296 kg and a battery capacity of 289.074 Ah, keeping the other assigned parameters fixed. I interpreted power-demand plots, calculated usable battery energy and compared the reported range and energy consumption at regeneration coefficients of 0.25 and 0.65.
Battery Energy
At a nominal pack voltage of 365 V, the battery stores approximately 105.51 kWh. The model uses a state-of-charge window from 93% to 7%, giving approximately 90.74 kWh of usable energy. Energy consumption is calculated by dividing usable energy by the simulated distance.
Reported Simulation Results
At a regeneration coefficient of 0.25, Drive Cycle 1 gives 277.01 miles and 0.3276 kWh/mile. Raising the coefficient to 0.65 gives 291.08 miles and 0.3117 kWh/mile: a 5.08% range increase and approximately 4.85% lower energy consumption. Drive Cycle 2 remains at 304.81 miles and 0.2977 kWh/mile in both reported runs.
Engineering Interpretation
Drive Cycle 1 shows more pronounced positive and negative power transients. Positive power corresponds to propulsion demand; negative power indicates regeneration during deceleration. Its reported improvement illustrates how braking opportunities affect energy recovery. Drive Cycle 2 shows no reported change, which warrants checking the cycle and model signals before attributing the result to a specific cause.
Scope and Limitations
These figures are results reported in the supplied coursework document. They describe the assigned simulation model, rather than measured road performance. Reproducing these runs requires the original model and driving-cycle files; the report screenshots alone do not validate the simulation.
Engineering Implications
Regeneration settings should be assessed against the braking opportunities of each driving cycle. The unchanged Cycle 2 result needs a signal and energy-balance check before it can support an explanation of the model behaviour.
Next Step
Review the model signals and integrated recovered energy for each cycle, then assess sensitivity to mass, battery assumptions and operating conditions against suitable reference data.
Reported Range Comparison
| Driving cycle | Regeneration coefficient | Range (miles) | Energy use (kWh/mile) |
|---|---|---|---|
| 1 | 0.25 | 277.01 | 0.3276 |
| 1 | 0.65 | 291.08 | 0.3117 |
| 2 | 0.25 | 304.81 | 0.2977 |
| 2 | 0.65 | 304.81 | 0.2977 |
Coursework Report
Source: Electric Vehicle Simulation using MATLAB/Simulink coursework report, Abdul Barek, University of Hertfordshire; submission date stated in the report: 17 April 2026.