Why This Topic Matters
A parallel hybrid-electric-vehicle powertrain with a rule-based supervisory controller that coordinates the engine, traction motor, battery and regenerative braking across a drive cycle.
For academic work, the model should connect every claimed improvement to a measurable output. A reliable workflow begins with a validated baseline, introduces one controlled modification at a time and uses repeatable scenarios for comparison.
Project Objective
Design and evaluate a transparent rule-based energy-management strategy that selects operating modes and power split while maintaining battery SOC, satisfying driver demand and reducing unnecessary engine operation.
Recommended MATLAB Simulink Blocks
- Driver model and standard or custom drive cycle
- Longitudinal vehicle dynamics and transmission
- Internal-combustion engine and fuel-consumption map
- Electric motor/generator and inverter
- Battery pack with SOC and power limits
- Rule-based supervisory controller and regenerative-braking logic
Step-by-Step Modelling Workflow
- Define vehicle and component ratings, battery limits and initial SOC.
- Create mode-selection rules from vehicle speed, demanded torque, SOC and braking command.
- Allocate engine and motor torque while enforcing component constraints.
- Run representative urban and highway cycles with consistent initial conditions.
- Compare fuel use, SOC trajectory, power split and regenerative-energy recovery.
Simulation Cases to Include
- Electric-only launch and low-load operation
- Engine-only cruising
- Hybrid assist during acceleration or hill climb
- Battery charging by engine/generator
- Regenerative braking and SOC-protection modes
Graphs and Results to Discuss
- Vehicle-speed tracking and demanded traction power
- Engine speed, torque, power and fuel consumption
- Motor/generator torque and electrical power
- Battery current, voltage, SOC and energy throughput
- Operating-mode timeline and regenerative-energy recovery
Do not report a curve only as “improved.” State the event time, compare the reference and measured signals, calculate relevant indices and explain the physical reason for the change.
PhD Novelty and FYP Extension Ideas
- Equivalent-consumption minimization strategy comparison
- Dynamic programming benchmark
- Fuzzy, ANN or reinforcement-learning energy management
- Battery-aging-aware power split
- Real drive-cycle and route-elevation integration
Where This Project Can Be Used
- Hybrid-vehicle PhD and master’s dissertations
- Automotive and mechatronics FYP projects
- Energy-management algorithm benchmarking
- Fuel-economy and battery-utilization studies
- Model-based control development for HEV powertrains
Common Modelling Mistakes
- Using inconsistent base values, units or sign conventions across subsystems.
- Tuning all control loops simultaneously instead of validating the inner loops first.
- Comparing controllers under different initial conditions or disturbances.
- Ignoring actuator, converter, current, SOC, temperature or power limits.
- Presenting scope screenshots without quantitative result interpretation.
Related Project Demonstration
The dedicated project page includes the uploaded MATLAB Simulink video, project scope, expected outputs and related research links.