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This study transforms vehicles into measurement systems for validating longitudinal vehicle and powertrain models using real traffic data. The calibrated model enables accurate energetic analysis and control strategy design.

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Area of Science:

  • Automotive Engineering
  • Control Systems
  • Energy Systems

Background:

  • Modern vehicles possess numerous sensors within onboard control and diagnostic systems, offering potential for data acquisition.
  • Inter-unit communication networks facilitate signal sharing, enabling external devices to record real-world traffic data.
  • Utilizing vehicle-generated data for model validation presents an efficient approach to understanding vehicle dynamics.

Purpose of the Study:

  • To validate a 1 Degree of Freedom (DOF) longitudinal vehicle and powertrain model using real-world traffic measurements.
  • To calibrate vehicle and drivetrain model parameters, including air drag, rolling resistance, and drivetrain efficiencies.
  • To establish validation criteria for speed tracking and cumulative energy tolerance.

Main Methods:

  • Transforming an up-to-date vehicle into a mobile measurement system by leveraging onboard sensors and communication networks.
  • Recording longitudinal vehicle data across three distinct city routes with varying road grades and directions for repeatability.
  • Employing a Differential GPS (DGPS) system to accurately record altitude changes during test drives.
  • Calibrating model parameters based on recorded measurements and validating against defined criteria (speed tracking, <10% cumulative energy tolerance).

Main Results:

  • Successful calibration of vehicle and drivetrain model parameters using recorded real-world data.
  • Validation of the 1 DOF longitudinal vehicle and powertrain model against speed tracking and energy balance criteria.
  • Demonstration of the model's readiness for subsequent energetic analysis and control strategy development.
  • Presentation of the energy balance for the applied driving cycles.

Conclusions:

  • The developed methodology effectively transforms vehicles into measurement systems for robust model validation.
  • The validated model provides a reliable tool for in-depth energetic analysis and the design of advanced control strategies.
  • The study confirms the feasibility of using onboard vehicle data for accurate powertrain and vehicle dynamics modeling.