Short answer

When simulating vehicle powertrains, especially those with advanced features, select a modelling fidelity that captures essential nonlinear behaviours to accurately predict dynamic performance and avoid potential issues like oscillations.

Field: Modelling
Source: Linköping electronic conference proceedings (2015)
Method: Simulation-based case study
Evidence: Strong effect

Increasing the complexity of gear models to include nonlinearities in losses and stiffness can reveal potential drive line oscillations that simpler models might miss. This modelling research insight is drawn from a 2015 study published in Linköping electronic conference proceedings. Using Simulation-based case study, researchers explored how this design variable affects real-world outcomes. The key design takeaway: When simulating vehicle powertrains, especially those with advanced features, select a modelling fidelity that captures essential nonlinear behaviours to accurately predict dynamic performance and avoid potential issues like oscillations.

Study

ModellingHigh ImpactStrong effect

Nonlinear Gear Models Reveal Drive Line Oscillation Tendencies

Increasing the complexity of gear models to include nonlinearities in losses and stiffness can reveal potential drive line oscillations that simpler models might miss.

Linköping electronic conference proceedings · 2015

Key Findings

01Increasing the complexity of gear models by incorporating nonlinearities in losses and stiffness leads to the identification of drive line oscillations.
02Simpler gear models with constant efficiency and stiffness may not reveal these oscillatory behaviours.

Application

Design takeaway

How to apply

When developing or simulating electric vehicle powertrains, especially those with torque vectoring, use simulation software that allows for nonlinear gear modelling. Start with a basic model and progressively increase complexity, observing how new phenomena like oscillations emerge.

Project actions

01When creating your simulation model, consider the key physical properties of the components you are modelling.
02Document the progression of your model's complexity and the impact of each addition on the simulation results.

Method & Evidence

AimTo investigate how different levels of detail in gear modelling affect the simulation of powertrain dynamics and the identification of drive line oscillations in a torque-vectoring electric vehicle.

MethodSimulation-based case study

ProcedureA gear model was developed in Modelica, incorporating features like losses, nonlinear elasticity, and forcing errors. This model was then used to simulate the dynamic behaviour of a torque-vectoring drive within a simplified vehicle model. The simulation was performed at various stages of detail, progressing from a basic model with fixed efficiency and constant spring stiffness to a more complex model with nonlinear losses and tooth stiffness. The simulation results were then analysed to identify tendencies towards drive line oscillation.

ContextElectric vehicle powertrain design and simulation

Variables

IVLevel of detail in gear modelling (e.g., linear vs. nonlinear losses and stiffness)

DVPresence and characteristics of drive line oscillations

CVVehicle model simplification, torque-vectoring drive configuration, simulation environment (Modelica)

Strengths & Limitations

Strengths

+Systematic increase in model complexity.
+Demonstration of how modelling choices impact simulation outcomes.

Limitations

The complexity of the simulation software and the time required to develop and run detailed models can be a constraint.

Reliability & validity

The validity of the findings is dependent on the accuracy of the Modelica library and the specific parameters used for the gear model. Reliability would be assessed by repeating simulations with identical parameters.

Think critically

How might the computational cost of more complex models influence a designer's decision on the level of detail to employ in a real-world design project?

Design Principles

"Model complexity should be commensurate with the phenomena being investigated to ensure accurate prediction of system behaviour."

Accurate modelling of powertrain components is crucial for predicting vehicle behaviour, especially in advanced systems like torque-vectoring drives. Understanding how model fidelity impacts simulation results allows designers to make informed decisions about the level of detail required for effective design and control system development.

What This Means for Your Design

Making your computer model of car gears more realistic by adding details about how they bend and lose energy can help you spot wobbles or shakes (oscillations) that simpler models might miss.

How to use in your project

1.Reference this study when justifying the choice of modelling detail for your design project's simulations, especially if you encounter unexpected dynamic behaviours.

Add to My Project

Quick Cite

Paragraph starter

The study by van der Linden and Tobolář (2015) highlights the critical role of modelling fidelity in predicting system dynamics. Their work demonstrates that incorporating nonlinearities in gear models, such as varying losses and tooth stiffness, can reveal drive line oscillations that are not apparent in simpler, linear models. This underscores the importance of selecting an appropriate level of modelling detail in design projects to accurately capture potential performance issues and ensure robust design outcomes.

Source

Linköping electronic conference proceedings

Modelling of Torque-Vectoring Drives for Electric Vehicles: a Case Study

journal · 2015

View source

Questions About This Research

What does the research say about nonlinear gear models reveal drive line oscillation tendencies?: When simulating vehicle powertrains, especially those with advanced features, select a modelling fidelity that captures essential nonlinear behaviours to accurately predict dynamic performance and avoid potential issues like oscillations. Evidence: Linköping electronic conference proceedings (2015).
Why does "Nonlinear Gear Models Reveal Drive Line Oscillation Tendencies" matter for design?: Accurate modelling of powertrain components is crucial for predicting vehicle behaviour, especially in advanced systems like torque-vectoring drives. Understanding how model fidelity impacts simulation results allows designers to make informed decisions about the level of detail required for effective design and control system development.
How can designers apply this research?: When simulating vehicle powertrains, especially those with advanced features, select a modelling fidelity that captures essential nonlinear behaviours to accurately predict dynamic performance and avoid potential issues like oscillations.
What were the main findings?: Increasing the complexity of gear models by incorporating nonlinearities in losses and stiffness leads to the identification of drive line oscillations.. Simpler gear models with constant efficiency and stiffness may not reveal these oscillatory behaviours.
What research method was used?: Simulation-based case study.
How strong is the evidence?: Evidence strength is rated Strong effect, based on a 2015 journal from Linköping electronic conference proceedings.
What should I do differently in my next project?: When developing or simulating electric vehicle powertrains, especially those with torque vectoring, use simulation software that allows for nonlinear gear modelling. Start with a basic model and progressively increase complexity, observing how new phenomena like oscillations emerge.
What are the limitations?: The study utilized a simplified vehicle model, and the findings may vary with more complex vehicle dynamics. The specific parameters and characteristics of the Modelica gear model might not be universally applicable without calibration.