Hybrid and Conventional Truck Powertrain Simulation
Purpose
Modern truck powertrains involve complex interactions between combustion engines, electric machines, and batteries.
This project focused on developing simulation models to evaluate system behavior, energy usage, and economic performance under realistic operating conditions.
Approach
I developed a system-level simulation framework to model hybrid and conventional truck powertrains, including:
- Energy flow between engine, electric motors, and battery
- Component behavior under varying load cases and duty cycles
- Regenerative braking and energy recovery
- Different control strategies for power management
The models were implemented using physics-based block diagram modeling (MATLAB/Simulink), with additional data processing and analysis in MATLAB and Python.
Example Analyses
- Comparison of hybrid vs conventional powertrains under different operating profiles
- Evaluation of engine on/off strategies versus battery charging strategies
- Sensitivity analysis on key parameters such as fuel cost, electricity price, and battery characteristics
Key Insights
- Identified operating strategies that improve overall system efficiency
- Highlighted trade-offs between fuel consumption, battery usage, and system complexity
- Demonstrated how control strategies significantly influence energy distribution and performance
Techno-Economic Evaluation
The simulation framework was extended to support decision-making through:
- Total Cost of Ownership (TCO) analysis
- Return on Investment (ROI) estimation
- Scenario-based evaluation of different powertrain configurations
This enabled comparison of alternative designs not only from a technical perspective but also from a cost and operational standpoint.
Engineering Relevance
This work supports:
- Early-stage design and comparison of powertrain concepts
- Optimization of control strategies for hybrid systems
- Evaluation of system-level trade-offs in energy and cost
Tools
MATLAB · Simulink · Python · Excel (TCO/ROI modeling)