EME 134: Vehicle Stability

Lab 3: Automobile Steering

Learning Objectives

After completing this lab you will be able to:

  • formulate the explicit first order ordinary differential equations for the lateral dynamics of an automobile
  • translate ordinary differential equations into a computer function that evaluates the equations at any given point in time
  • develop a function that evaluates state dependent input functions
  • develop a function that evaluates state and input dependent output variables
  • numerically integrate ordinary differential equations with Octave/Matlab's ode45
  • create complete and legible plots of the resulting input, state, and output trajectories
  • create a report with textual explanations and plots of the simulation

Information

Extra information (asides) are in blue boxes.

Warnings

Warnings are in yellow boxes.

Introduction

In this lab, you will investigate the planar dynamics of a car being steered through a lane change maneuver. The ability for the car to maneuver as expected given a steering input depends on the car's ability to generate and direct the lateral forces at the front and rear wheels. At a basic level the car designer can manipulate the car's geometry, weight distribution, tire type to control the base dynamics of the vehicle. The designer can then design and tune other aspects in the suspension system to obtain even better performance. You will investigate the dynamics without suspension considerations to get an understanding of the car's basic motion and performance in a lane change.

The following video gives an introduction to rear wheel steering that can provide some background to one of the simulations you will do:

System Description

You will model and simulate a car traveling on a planar surface. The car will be able to steer both the front wheels and rear wheels relative to the chassis. The normal force is assumed to be equal on all of the wheels, i.e. no load significant transfer from cornering. The tires will be assumed to be pure rolling and the vehicle's forward velocity is constant. The lateral forces at the wheels will be modeled using the linear relation to slip angle and thus the model is only valid for small yaw and slip angles. You will investigate the effects on vehicle behavior when it is setup as an understeering and oversteering car. This model is called the "bicycle model of the car". The derivation of the model and analysis are presented in Chapter 6 of the book.

Figure 1: Schematics of the lateral car dynamics model.

Equations of Motion

The equations of motion for the bicycle model of the car are presented below in the canonical linear form. The factor of 2 accounts for the combined affect of the pairs of tires at the front and rear, i.e. \(C_f\) and \(C_r\) are the cornering coefficients of the individual front and rear tires, respectively.

\begin{equation*} \begin{bmatrix} m & 0 \\ 0 & I \end{bmatrix} \begin{bmatrix} \dot{v} \\ \dot{\omega} \end{bmatrix} + \begin{bmatrix} 2(C_f + C_r)/U & 2(aC_f-bC_r)/U \\ 2(aC_f-bC_r)/U & 2(a^2C_f+b^2C_r)/U \end{bmatrix} \begin{bmatrix} v \\ \omega \end{bmatrix} + \begin{bmatrix} 0 & -2(C_f+C_r) \\ 0 & -2(aC_f-bC_r) \end{bmatrix} \begin{bmatrix} y \\ \psi \end{bmatrix} = \begin{bmatrix} 2C_f & 2C_r \\ 2C_f a & -2C_r b \end{bmatrix} \begin{bmatrix} \delta_f \\ \delta_r \end{bmatrix} \end{equation*}

These equations define expressions for the derivatives of the four time varying state variables \(y,v,\psi,\omega\) and the two time varying input variables \(\delta_f,\delta_r\) which are described below.

Symbol Description Units
\(y\) Lateral deviation of the car's mass center \(\textrm{m}\)
\(\psi\) Yaw angle of the car \(\textrm{rad}\)
\(v=\dot{y}\) Lateral velocity of the car's mass center \(\textrm{m/s}\)
\(\omega=\dot{\psi}\) Yaw angular rate of the car \(\textrm{rad/s}\)
\(\delta_f\) Steer angle of the front wheels \(\textrm{rad}\)
\(\delta_r\) Steer angle of the rear wheels \(\textrm{rad}\)

You will need to write these equations of motion as four explicit ordinary differential equations in first order form for your state derivative function. You will use the section Defining the State Derivative Function for these equations.

Inputs

The front \(\delta_f\) and rear \(\delta_r\) steering angles can be set to desired functions of time in your input function. You will setup two input functions that will steer the automobile through a lane change using for these scenarios:

Only front steering
Create a function that steers the front wheels to \(\delta\) degrees for \(2\leq t \leq 4\) and then \(-\delta\) for \(6\leq t \leq 8\) seconds where \(\delta\) is the magnitude of the steering pulse.
Front and rear steering
Create a function that steers the front wheels to \(\delta\) degrees for \(2\leq t \leq 4\) and then \(-\delta\) for \(6\leq t \leq 8\) seconds and simultaneously steers the rear wheels in the opposite direct the same amounts.

See Time Varying Inputs for more information.

Outputs

The output function should return all of the state variables, the two steering angle inputs, the combined lateral force at the front and rear tires, the travel distance in the \(x\) direction, and the lateral acceleration. The lateral forces at the combined tires can be calculated with:

\begin{align*} F_{yf} = & 2C_f \alpha_f \\ \alpha_f = & \frac{v + a\omega}{U} - \psi - \delta_f \\ F_{yr} = & 2C_r \alpha_r \\ \alpha_r = & \frac{v - b\omega}{U} - \psi - \delta_r \end{align*}

Your state derivative function can calculate the lateral acceleration. You will use the section Outputs Other Than The States to compute these values.

Constant Parameters

The majority of the variables in the differential equations and input equations above do not vary with time, i.e. they are constant. Below is a table with an explanation of each variable, its value, and its units. Note that the units are a self consistent set of SI base units.

Symbol Description Value Units
\(U\) Forward speed \(10,20,30\) \(m/s\)
\(\delta\) Magnitude of the steer angle 1 \(\textrm{deg}\)
\(I\) Car yaw moment of inertia (assumes inertia of a rectangle) \(\frac{m}{12}(w^2+l^2)\) \(\textrm{kg}\cdot\textrm{m}^2\)
\(d\mu_y/d\alpha\) Slope of friction vs slip angle curve at \(\alpha=0\) 7.0 Unitless
\(g\) Acceleration due to gravity 9.81 \(\textrm{m/s}^2\)
\(m\) Mass of the car 1200 \(\textrm{kg}\)
\(w\) Track 1.54 \(\textrm{m}\)
\(l\) Wheelbase 2.7 \(\textrm{m}\)
\(r\) Ratio of \(a/l\) \(0<r<1\) \(\textrm{unitless}\)
\(a\) Distance from mass center to front axle \(rl\) \(\textrm{m}\)
\(b\) Distance from mass center to rear axle \((1-r)l\) \(\textrm{m}\)
\(F_{zf}\) Total normal force at the front wheels \(F_z/2\) \(\textrm{N}\)
\(F_{zr}\) Total normal force at the rear wheels \(F_z/2\) \(\textrm{N}\)
\(C_f\) Cornering coefficient for a single front wheel. Calculate based on details in Chapter 4. \(\textrm{N/rad}\)
\(C_r\) Cornering coefficient for a single rear wheel. Calculate based on details in Chapter 4. \(\textrm{N/rad}\)

You will use the section Integrating the Equations to for these values.

Initial Conditions

The initial condition will be the equilibrium state of the vehicle, i.e. all initial conditions equal to zero. See Integrating the Equations for how to set up the initial condition vector. Make sure that your initial conditions are arranged in the same order as your state variables.

Time Steps

Simulate the system for 10 seconds with time steps of 1/100th of a second.

Understeer, Oversteer, and Neutralsteer

An automobile can be classified as oversteer, understeer, or neutralsteer based on relationship between lateral force generation at the front and rear for the vehicle. The so called understeer coefficient \(K\) determines whether a given car is one of the three:

\begin{equation*} K = \frac{m(bC_r-aC_f)}{(a+b)C_fC_r} \end{equation*}

If \(K > 0\) the car is an understeer; if \(K < 0\) the car is oversteer; and if \(K=0\) the car is neutral steer. Note that these characterizations only depend on \(m,a,b,C_f,C_r\). You will need to indicate the values of \(K\) that you calculate for each scenario and specify if the car is over, under, or neutral.

Deliverables

In your lab report, show your work for creating and evaluating the simulation model. Include any calculations you had to do, for example those for state equations, initial conditions, input equations, time parameters, and any other parameters. Additionally, provide the indicated plots and answer the questions below. Append a copy of your Matlab/Octave code to the end of the report. The report should follow the report template and guidelines.

Submit a report as a single PDF file to Canvas by the due date that addresses the following items:

  1. Create a function defined in an m-file that evaluates the right hand side of the ODEs, i.e. evaluates the state derivatives. See Defining the State Derivative Function for an explanation.
  2. Create two functions defined each in an m-file that calculates the two requested inputs: front steer and dual steer. See Time Varying Inputs for an explanation.
  3. Create a function defined in an m-file that calculates the requested outputs. See Outputs Other Than the States and Outputs Involving State Derivatives for an explanation.
  4. Create a script in an m-file that utilizes the above functions to simulate system for three comparison scenarios described below. This should setup the constants, integrate the dynamics equations, and plot each state, and output versus time. See Integrating the Equations for an explanation.
  5. Compare the lane change steering behavior with \(\delta=1\) deg of the car for an understeer and oversteer configuration at speeds \(U=10\) m/s using only front steering. Select a value of \(r\) to obtain a suitable \(K\) for each vehicle. Describe the differences in the state and output trajectories. Comment on why the terms "understeer" and "oversteer" are used to describe the configurations.
  6. Repeat #5 with \(U=30\) m/s.
  7. Compare the lane change steering behavior with \(\delta=1\) deg of an understeer car traveling at \(U=20\) m/s for the front steering vs the dual front-rear steering. Describe the differences in the state and output trajectories. Comment on whether a dual steering has an any advantages or disadvantages based on the simulation results.

Tips

  • When plotting the path of the mass center \(y(x)\) use the axis('image') command to set the aspect ratio.

Assessment Rubric

Score will be between 50 and 100.
Topic [10 pts] Exceeds expectations [5 pts] Meets expectatoins [0 pts] Does not meet expectations
Functions All Matlab/Octave functions are present and take correct inputs and produce the expected outputs. Some of the functions are present and mostly take correct inputs and produce the expected outputs No functions are present or not working at all.
Main Script Constant parameters only defined once in main script(s); Integration produces the correct state, input, and output trajectories; Good choices in number of time steps and resolution are chosen and justified. Parameters are defined in multiple places; Integration produces some correct state, input, and output trajectories; Poor choices in number of time steps and resolution are chosen Constants defined redundantly; Integration produces incorrect trajectories; Poor choices in time duration and steps
Explanations Explanation of three simulation comparisons are correct and well explained; Plots of appropriate variables are used in the explanations Explanation of three simulation comparisons is somewhat correct and reasonably explained; Plots of appropriate variables are used in the explanations, but some are missing Explanation of three simulations are incorrect and poorly explained; Plots are missing
Report and Code Formatting All axes labeled with units, legible font sizes, informative captions; Functions are documented with docstrings which fully explain the inputs and outputs; Professional, very legible, quality writing; All report format requirements met Some axes labeled with units, mostly legible font sizes, less-than-informative captions; Functions have docstrings but the inputs and outputs are not fully explained; Semi-professional, somewhat legible, writing needs improvement; Most report format requirements met Axes do not have labels, legible font sizes, or informative captions; Functions do not have docstrings; Report is not professionally written and formatted; Report format requirements are not met
Contributions Clear that all team members have made equitable contributions. Not clear that contributions were equitable and you need to improve balance of contributions. No indication of equitable contributions.