Background
There are several different computer-aided engineering (CAE) tools in the market to assist engineers in modeling vehicle and component-level performance under various driving conditions. However, few, if any, CAE tools allow a user to evaluate the thermal and mechanical performance while also considering a vehicle’s unique control strategy. The objective of this project was to use two CAE tools to co-simulate the vehicles performance and control strategy to assist in selecting and sizing the optimal hybrid architecture for this vehicle and duty cycle.
Approach
This effort was broken into several tasks focused to improve the performance model and, later, simulate the preliminary control strategy in conjunction with the performance model. The performance model was improved by parameterizing the mechanical and thermal characteristics of key powertrain components such as engine, battery and electric machine.
With the mechanical and thermal modeling complete, optimization of the power split between the engine and electric motor could be conducted to assist in setting a high-level control strategy for the vehicle using a cost function based on energy consumption.
A preliminary software architecture was implemented in another CAE tool. This software included a more detailed view of the controls including power-up sequences, safety monitors, diagnostics, etc. that was previously lacking in the performance model. With both CAE tools setup and calibrated, the framework to co-simulate both was developed to help in the hybrid architecture selection and sizing.
Accomplishments
The co-simulated CAE tools were setup to allow for easy parametrization of the models such that they can be adjusted to simulate several different architectures, hardware, and controls strategies. For this application, the battery pack, motor/inverter, on-board charger, and DC-DC converter was sized and selected.
The model output indicated a P2 hybrid architecture was the most optimal solution based off the energy consumption of the system, and the controls strategy should leverage the electric hybrid system at lower speeds and use the natural gas engine at higher speeds and where the electric motor is incapable of supporting the driver demands.
Additional work is on-going to continue to refine the controls strategy and add more component and system-level diagnostics while using this tool chain to gauge the effectiveness of these changes.