Longitudinal Driver

Longitudinal speed-tracking controller

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Libraries:
Powertrain Blockset / Vehicle Scenario Builder
Vehicle Dynamics Blockset / Vehicle Scenarios / Driver

Description

TheLongitudinal Driverblock implements a longitudinal speed-tracking controller. Based on reference and feedback velocities, the block generates normalized acceleration and braking commands that can vary from 0 through 1. You can use the block to model the dynamic response of a driver or to generate the commands necessary to track a longitudinal drive cycle.

Configurations

External Actions

Use theExternal Actionsparameters to create input ports for signals that can disable, hold, or override the closed-loop acceleration or deceleration commands. The block uses this priority order for the input commands: disable (highest), hold, override.

This table summarizes the external action parameters.

Goal	External Action Parameter	Input Ports	Data Type
Override the accelerator command with an input acceleration command.	Accelerator override	`EnablAccelOvr`	`Boolean`
	Accelerator override	`AccelOvrCmd`	`double`
Hold the acceleration command at the current value.	Accelerator hold	`AccelHld`	`Boolean`
Disable the acceleration command.	Accelerator disable	`AccelZero`	`Boolean`
Override the decelerator command with an input deceleration command.	Decelerator override	`EnablDecelOvr`	`Boolean`
	Decelerator override	`DecelOvrCmd`	`double`
Hold the decelerator command at current value.	Decelerator hold	`DecelHld`	`Boolean`
Disable the decelerator command.	Decelerator disable	`DecelZero`	`Boolean`

Controller

Use theControl type, cntrlTypeparameter to specify one of these control options.

Setting	Block Implementation
`PI`	Proportional-integral (PI) control with tracking windup and feed-forward gains.
`Scheduled PI`	PI control with tracking windup and feed-forward gains that are a function of vehicle velocity.
`Predictive`	Optimal single-point preview (look ahead) control model developed by C. C. MacAdam^{1, 2, 3}。The model represents driver steering control behavior during path-following and obstacle avoidance maneuvers. Drivers preview (look ahead) to follow a predefined path. To implement the MacAdam model, the block: Represents the dynamics as a linear single track (bicycle) vehicle Minimizes the previewed error signal at a single pointT*seconds ahead in time Accounts for the driver lag deriving from perceptual and neuromuscular mechanisms

Setting

Block Implementation

PI

Proportional-integral (PI) control with tracking windup and feed-forward gains.

Scheduled PI

PI control with tracking windup and feed-forward gains that are a function of vehicle velocity.

Predictive

Optimal single-point preview (look ahead) control model developed by C. C. MacAdam^{1, 2, 3}。The model represents driver steering control behavior during path-following and obstacle avoidance maneuvers. Drivers preview (look ahead) to follow a predefined path. To implement the MacAdam model, the block:

Represents the dynamics as a linear single track (bicycle) vehicle
Minimizes the previewed error signal at a single pointT*seconds ahead in time
Accounts for the driver lag deriving from perceptual and neuromuscular mechanisms

Shift

Use theShift type, shftTypeparameter to specify one of these shift options.

Setting	Block Implementation
`None`	No transmission. Block outputs a constant gear of 1. Use this setting to minimize the number of parameters you need to generate acceleration and braking commands to track forward vehicle motion. This setting does not allow reverse vehicle motion.
`Reverse, Neutral, Drive`	Block uses a Stateflow^®chart to model reverse, neutral, and drive gear shift scheduling. Use this setting to generate acceleration and braking commands to track forward and reverse vehicle motion using simple reverse, neutral, and drive gear shift scheduling. Depending on the vehicle state and vehicle velocity feedback, the block uses the initial gear and time required to shift to shift the vehicle up into drive or down into reverse or neutral. 中性的齿轮,块使用刹车commands to control the vehicle speed. For reverse gears, the block uses an acceleration command to generate torque and a brake command to reduce vehicle speed.
`Scheduled`	Block uses a Stateflow chart to model reverse, neutral, park, and N-speed gear shift scheduling. Use this setting to generate acceleration and braking commands to track forward and reverse vehicle motion using reverse, neutral, park, and N-speed gear shift scheduling. Depending on the vehicle state and vehicle velocity feedback, the block uses these parameters to determine the: Initial gear Upshift and downshift accelerator pedal positions Upshift and downshift velocity Timing for shifting and engaging forward and reverse from neutral 中性的齿轮,块使用刹车commands to control the vehicle speed. For reverse gears, the block uses an acceleration command to generate torque and a brake command to reduce vehicle speed.
`External`	Block uses the input gear, vehicle state, and velocity feedback to generate acceleration and braking commands to track forward and reverse vehicle motion. 中性的齿轮,块使用刹车commands to control the vehicle speed. For reverse gears, the block uses an acceleration command to generate torque and a brake command to reduce vehicle speed.

Gear Signal

Use theOutput gear signalparameter to create theGearCmdoutput port. TheGearCmdsignal contains the integer value of the commanded vehicle gear.

Gear	Integer
Park	`80`
Reverse	`-1`
Neutral	`0`
Drive	`1`
Gear	`Gear number`

Controller: PI Speed-Tracking

If you set the control type toPIorScheduled PI,block implements proportional-integral (PI) control with tracking windup and feed-forward gains. For theScheduled PIconfiguration, the block uses feed forward gains that are a function of vehicle velocity.

To calculate the speed control output, the block uses these equations.

Setting	Equation
`PI`	$y = \frac{K_{f f}}{v_{n o m}} v_{r e f} + \frac{K_{p} e_{r e f}}{v_{n o m}} + \int (\frac{K_{i} e_{r e f}}{v_{n o m}} + K_{a w} e_{o u t}) d t + K_{g} θ$
`Scheduled PI`	$y = \frac{K_{f f} (v)}{v_{n o m}} v_{r e f} + \frac{K_{p} (v) e_{r e f}}{v_{n o m}} + \int (\frac{K_{i} (v) e_{r e f}}{v_{n o m}} + K_{a w} e_{o u t}) e_{r e f} d t + K_{g} (v) θ$

Setting

Equation

PI

$y = \frac{K_{f f}}{v_{n o m}} v_{r e f} + \frac{K_{p} e_{r e f}}{v_{n o m}} + \int (\frac{K_{i} e_{r e f}}{v_{n o m}} + K_{a w} e_{o u t}) d t + K_{g} θ$

Scheduled PI

$y = \frac{K_{f f} (v)}{v_{n o m}} v_{r e f} + \frac{K_{p} (v) e_{r e f}}{v_{n o m}} + \int (\frac{K_{i} (v) e_{r e f}}{v_{n o m}} + K_{a w} e_{o u t}) e_{r e f} d t + K_{g} (v) θ$

$\begin{array}{l} where: \\ e_{r e f} = v_{r e f} - v \\ e_{o u t} = y_{s a t} - y \\ y_{s a t} = {\begin{matrix} - 1 & y < - 1 \\ y & - 1 \leq y \leq 1 \\ 1 & 1 < y \end{matrix} \end{array}$

The velocity error low-pass filter uses this transfer function.

$H (s) = \frac{1}{τ_{e r r} s + 1} for τ_{e r r} > 0$

To calculate the acceleration and braking commands, the block uses these equations.

$\begin{array}{l} y_{a c c} = {\begin{matrix} 0 & y_{s a t} < 0 \\ y_{s a t} & 0 \leq y_{s a t} \leq 1 \\ 1 & 1 < y_{s a t} \end{matrix} \\ y_{d e c} = {\begin{matrix} 0 & y_{s a t} > 0 \\ - y_{s a t} & - 1 \leq y_{s a t} \leq 0 \\ 1 & y_{s a t} < - 1 \end{matrix} \end{array}$

The equations use these variables.

v_nom	Nominal vehicle speed
K_p	Proportional gain
K_i	Integral gain
K_aw	Anti-windup gain
K_ff	Velocity feed-forward gain
K_g	Grade angle feed-forward gain
θ	Grade angle
τ_err	Error filter time constant
y	Nominal control output magnitude
y_sat	Saturated control output magnitude
e_ref	Velocity error
e_out	Difference between saturated and nominal control outputs
y_acc	Acceleration signal
y_12月	Braking signal
v	Velocity feedback signal
v_ref	Reference velocity signal

Controller: Predictive Speed-Tracking

If you set theControl type, cntrlTypeparameter toPredictive,block implements an optimal single-point preview (look ahead) control model developed by C. C. MacAdam^{1, 2, 3}。The model represents driver steering control behavior during path-following and obstacle avoidance maneuvers. Drivers preview (look ahead) to follow a predefined path. To implement the MacAdam model, the block:

Represents the dynamics as a linear single track (bicycle) vehicle
Minimizes the previewed error signal at a single point T* seconds ahead in time
Accounts for the driver lag deriving from perceptual and neuromuscular mechanisms

Vehicle Dynamics

For longitudinal motion, the block implements these linear dynamics.

$\begin{array}{l} x_{1} = v \\ {\dot{x}}_{1} = x_{2} = \frac{K_{p t}}{m} - g \sin (γ) + F_{r} x_{1} \end{array}$

In matrix notation:

$\begin{array}{l} \dot{x} = F x + g \bar{u} \\ where: \\ x = [\begin{matrix} x_{1} \\ x_{2} \end{matrix}] \\ F = [\begin{matrix} 0 & 1 \\ \frac{F_{r}}{m} & 0 \end{matrix}] \\ g = [\begin{matrix} \begin{matrix} 0 \\ \frac{K_{p t}}{m} \end{matrix} \end{matrix}] \\ \bar{u} = u - \frac{m^{2}}{K_{p t}} g sin (γ) \end{array}$

The block uses this equation for the rolling resistance.

$F_{r} = - [\tanh (x_{1}) (\frac{a_{r}}{x_{1}} + c_{r} x_{1}) + b_{r}]$

The single-point model assumes a minimum previewed error signal at a single pointT*seconds ahead in time.a*is the driver ability to predict the future vehicle response based on the current steering control input.b*is the driver ability to predict the future vehicle response based on the current vehicle state. The block uses these equations.

$\begin{array}{l} a * = (T *) m^{T} [I + \sum_{n = 1}^{\infty} \frac{F^{n} {(T *)}^{n}}{(n + 1)!}] g e \\ b * = m^{T} [I + \sum_{n = 1}^{\infty} \frac{F^{n} {(T *)}^{n}}{n!}] \\ where: \\ m^{T} = [\begin{matrix} 1 & 1 \end{matrix}] \end{array}$

The equations use these variables.

a,b	Forward and rearward tire location, respectively
m	Vehicle mass
I	Vehicle rotational inertia
a,b	Driver prediction scalar and vector gain, respectively
x	Predicted vehicle state vector
v	Longitudinal velocity
F	System matrix
K_pt	Tractive force and brake limit
γ	Grade angle
g	Control coefficient vector
g	Gravitational constant
T*	Preview time window
ƒ(t+T)*	Previewed path input T* seconds ahead
U	Forward vehicle velocity
*m^T*	Constant observer vector; provides vehicle lateral position
F_r	Rolling resistance
a_r	Static rolling and driveline resistance
b_r	Linear rolling and driveline resistance
c_r	Aerodynamic rolling and driveline resistance

Optimization

The single-point model implemented by the block finds the steering command that minimizes a local performance index,J, over the current preview interval, (t,t+T).

$J = \frac{1}{T} \int_{t}^{t + T} {[f (η) - y (η)]}^{2} d η$

To minimizeJwith respect to the steering command, this condition must be met.

$\frac{d J}{d u} = 0$

You can express the optimal control solution in terms of a current non-optimal and corresponding nonzero preview output errorT*seconds ahead^{1, 2, 3}。

$u^{o} (t) = u (t) + \frac{e (t + T^{*})}{a^{*}}$

The block uses the preview distance and vehicle longitudinal velocity to determine the preview time window.

$T^{*} = \frac{L}{U}$

The equations use these variables.

T*	Preview time window
ƒ(t+T)*	Previewed path inputT*sec ahead
y(t+T)*	Previewed plant outputT*sec ahead
e(t+T)*	Previewed error signalT*sec ahead
u(t),u^o(t)	Steer angle and optimal steer angle, respectively
L	Preview distance
J	Performance index
U	Forward (longitudinal) vehicle velocity

Driver Lag

The single-point model implemented by the block introduces a driver lag. The driver lag accounts for the delay when the driver is tracking tasks. Specifically, it is the transport delay deriving from perceptual and neuromuscular mechanisms. To calculate the driver transport delay, the block implements this equation.

$H (s) = e^{- s τ}$

The equations use these variables.

τ	Driver transport delay
y(t+T)*	Previewed plant outputT*sec ahead
e(t+T)*	Previewed error signalT*sec ahead
u(t),u^o(t)	Steer angle and optimal steer angle, respectively
J	Performance index

Ports

Input

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VelRef—Reference vehicle velocity
`scalar`

Reference velocity,v_ref, in m/s.

EnblAccelOvr—Enable acceleration command override
`scalar`

Enable acceleration command override.

Dependencies

To enable this port, selectAcceleration override。

Data Types:Boolean

AccelOvrCmd—Acceleration override command
`scalar`

Acceleration override command, normalized from 0 through 1.

Dependencies

To enable this port, selectAcceleration override。

Data Types:double

AccelHld—Acceleration hold
`scalar`

Boolean signal that holds the acceleration command at the current value.

Dependencies

To enable this port, selectAcceleration hold。

Data Types:Boolean

AccelZero—Disable acceleration command
`scalar`

Disable acceleration command.

Dependencies

To enable this port, selectAcceleration disable。

Data Types:Boolean

EnblDecelOvr—Enable deceleration command override
`scalar`

Enable deceleration command override.

Dependencies

To enable this port, selectDeceleration override。

Data Types:Boolean

DecelOvrCmd—Deceleration override command
`scalar`

Deceleration override command, normalized from 0 through 1.

Dependencies

To enable this port, selectDeceleration override。

Data Types:double

DecelHld—Deceleration hold
`scalar`

Boolean signal that holds the deceleration command at the current value.

Dependencies

To enable this port, selectDeceleration hold。

Data Types:Boolean

DecelZero—Disable deceleration command
`scalar`

Disable deceleration command.

Dependencies

To enable this port, selectDeceleration disable。

Data Types:Boolean

ExtGear—Gear
`scalar`

Gear	Integer
Park	`80`
Reverse	`-1`
Neutral	`0`
Drive	`1`
Gear	`Gear number`

Dependencies

To enable this port, setShift type, shftTypetoExternal。

VelFdbk—Longitudinal vehicle velocity
`scalar`

Longitudinal vehicle velocity,U, in the vehicle-fixed frame, in m/s.

Grade—Road grade angle
`scalar`

Road grade angle,θorγ, in deg.

Output

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Info—Bus signal
bus

Bus signal containing these block calculations.

Signal		Variable	Description
`Accel`		y_acc	Commanded vehicle acceleration, normalized from 0 through 1
`Decel`		y_12月	Commanded vehicle deceleration, normalized from 0 through 1
`Gear`			Integer value of commanded gear
`Clutch`			Clutch command
`Err`		e_ref	Difference in reference vehicle speed and vehicle speed
`ErrSqrSum`		$\int_{0}^{t} e_{r e f}^{2} d t$	Integrated square of error
`ErrMax`		$\max (e_{r e f} (t))$	Maximum error during simulation
`ErrMin`		$\min (e_{r e f} (t))$	Minimum error during simulation
`ExtActions`	`EnblAccelOvr`		Override the accelerator command with an input acceleration command
	`AccelOvrCmd`		Input accelerator override command
	`AccelHld`		Hold the acceleration command at the current value
	`AccelZero`		Disable the acceleration command
	`EnblDecelOvr`		Override the decelerator command with an input deceleration command
	`DecelOvrCmd`		Input deceleration override command
	`DecelHld`		Hold the decelerator command at current value
	`DecelZero`		Disable the decelerator command

AccelCmd—Commanded vehicle acceleration
`scalar`

Commanded vehicle acceleration,y_acc, normalized from 0 through 1.

DecelCmd—Commanded vehicle deceleration
`scalar`

Commanded vehicle deceleration,y_12月, normalized from 0 through 1.

GearCmd—Commanded vehicle gear
`scalar`

Integer value of commanded vehicle gear.

Gear	Integer
Park	`80`
Reverse	`-1`
Neutral	`0`
Drive	`1`
Gear	`Gear number`

Dependencies

To enable this port, selectOutput gear signal。

Parameters

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External Actions

Accelerator override—Override acceleration command
`off`(default) |`on`

Select to override the acceleration command with an input acceleration command.

Dependencies

Selecting this parameter creates theEnblAccelOvrandAccelOvrCmdinput ports.

Accelerator hold—Hold acceleration command
`off`(default) |`on`

Select to hold the acceleration command.

Dependencies

Selecting this parameter creates theAccelHldinput port.

Accelerator disable—Disable acceleration command
`off`(default) |`on`

Select to disable the acceleration command.

Dependencies

Selecting this parameter creates theAccelZeroinput port.

Decelerator override—Override deceleration command
`off`(default) |`on`

Select to override the deceleration command with an input deceleration command.

Dependencies

Selecting this parameter creates theEnblDecelOvrandDecelOvrCmdinput ports.

Decelerator hold—Hold deceleration command
`off`(default) |`on`

Select to hold the deceleration command.

Dependencies

Selecting this parameter creates theDecelHldinput port.

Decelerator disable—Disable deceleration command
`off`(default) |`on`

Select to disable the deceleration command.

Dependencies

Selecting this parameter creates theDecelZeroinput port.

Configuration

Control type, cntrlType—Longitudinal control
`PI`(default) |`Scheduled PI`|`Predictive`

Type of longitudinal control.

Setting	Block Implementation
`PI`	Proportional-integral (PI) control with tracking windup and feed-forward gains.
`Scheduled PI`	PI control with tracking windup and feed-forward gains that are a function of vehicle velocity.
`Predictive`	Optimal single-point preview (look ahead) control model developed by C. C. MacAdam^{1, 2, 3}。The model represents driver steering control behavior during path-following and obstacle avoidance maneuvers. Drivers preview (look ahead) to follow a predefined path. To implement the MacAdam model, the block: Represents the dynamics as a linear single track (bicycle) vehicle Minimizes the previewed error signal at a single pointT*seconds ahead in time Accounts for the driver lag deriving from perceptual and neuromuscular mechanisms

Setting

Block Implementation

PI

Proportional-integral (PI) control with tracking windup and feed-forward gains.

Scheduled PI

PI control with tracking windup and feed-forward gains that are a function of vehicle velocity.

Predictive

Represents the dynamics as a linear single track (bicycle) vehicle
Minimizes the previewed error signal at a single pointT*seconds ahead in time
Accounts for the driver lag deriving from perceptual and neuromuscular mechanisms

Shift type, shftType—Shift type
`None`(default) |`Reverse, Neutral, Drive`|`Scheduled`|`External`

Shift type.

Setting	Block Implementation
`None`	No transmission. Block outputs a constant gear of 1. Use this setting to minimize the number of parameters you need to generate acceleration and braking commands to track forward vehicle motion. This setting does not allow reverse vehicle motion.
`Reverse, Neutral, Drive`	Block uses a Stateflow chart to model reverse, neutral, and drive gear shift scheduling. Use this setting to generate acceleration and braking commands to track forward and reverse vehicle motion using simple reverse, neutral, and drive gear shift scheduling. Depending on the vehicle state and vehicle velocity feedback, the block uses the initial gear and time required to shift to shift the vehicle up into drive or down into reverse or neutral. 中性的齿轮,块使用刹车commands to control the vehicle speed. For reverse gears, the block uses an acceleration command to generate torque and a brake command to reduce vehicle speed.
`Scheduled`	Block uses a Stateflow chart to model reverse, neutral, park, and N-speed gear shift scheduling. Use this setting to generate acceleration and braking commands to track forward and reverse vehicle motion using reverse, neutral, park, and N-speed gear shift scheduling. Depending on the vehicle state and vehicle velocity feedback, the block uses these parameters to determine the: Initial gear Upshift and downshift accelerator pedal positions Upshift and downshift velocity Timing for shifting and engaging forward and reverse from neutral 中性的齿轮,块使用刹车commands to control the vehicle speed. For reverse gears, the block uses an acceleration command to generate torque and a brake command to reduce vehicle speed.
`External`	Block uses the input gear, vehicle state, and velocity feedback to generate acceleration and braking commands to track forward and reverse vehicle motion. 中性的齿轮,块使用刹车commands to control the vehicle speed. For reverse gears, the block uses an acceleration command to generate torque and a brake command to reduce vehicle speed.

Reference and feedback units, velUnits—Velocity units
m/s (default)

Vehicle velocity reference and feedback units.

Dependencies

If you setControl type, cntrlTypecontrol type toScheduledorScheduled PI,block uses theReference and feedback units, velUnitsfor theNominal speed, vnomparameter dimension.

If you setShift Type, shftTypetoScheduled,block uses theLongitudinal velocity units, velUnitsfor these parameter dimensions:

Upshift velocity data table, upShftTbl
Downshift velocity data table, dwnShftTbl

Output gear signal—Create`GearCmd`output port
`off`(default) |`on`

指定创造e output portGearCmd。

Control

Longitudinal

Proportional gain, Kp—Gain
`10`(default) |`scalar`

Proportional gain,K_p, dimensionless.

Dependencies

To create this parameter, setControl typetoPI。

Integral gain, Ki—Gain
`5`(default) |`scalar`

Proportional gain,K_i, dimensionless.

Dependencies

To create this parameter, setControl typetoPI。

Velocity feed-forward, Kff—Gain
`。1`(default) |`scalar`

Velocity feed-forward gain,K_ff, dimensionless.

Dependencies

To create this parameter, setControl typetoPI。

Grade angle feed-forward, Kg—Gain
`0`(default) |`scalar`

Grade angle feed-forward gain,K_g, in 1/deg.

Dependencies

To create this parameter, setControl typetoPI。

Velocity gain breakpoints, VehVelVec—Breakpoints
`[0 100]`(default) |`vector`

Velocity gain breakpoints,VehVelVec, dimensionless.

Dependencies

To create this parameter, setControl typetoScheduled PI。

Velocity feed-forward gain values, KffVec—Gain
`[.1 .1]`(default) |`vector`

Velocity feed-forward gain values,KffVec, as a function of vehicle velocity, dimensionless.

Dependencies

To create this parameter, setControl typetoScheduled PI。

Proportional gain values, KpVec—Gain
`[10 10]`(default) |`vector`

Proportional gain values,KpVec, as a function of vehicle velocity, dimensionless.

Dependencies

To create this parameter, setControl typetoScheduled PI。

Integral gain values, KiVec—Gain
`[5 5]`(default) |`vector`

Integral gain values,KiVec, as a function of vehicle velocity, dimensionless.

Dependencies

To create this parameter, setControl typetoScheduled PI。

Grade angle feed-forward values, KgVec—Grade gain
`[0 0]`(default) |`vector`

Grade angle feed-forward values,KgVec, as a function of vehicle velocity, in 1/deg.

Dependencies

To create this parameter, setControl typetoScheduled PI。

Nominal speed, vnom—Nominal vehicle speed
`5`(default) |`scalar`

Nominal vehicle speed,v_nom, in units specified by theReference and feedback units, velUnits参数。The block uses the nominal speed to normalize the controller gains.

Dependencies

To create this parameter, setControl typetoPIorScheduled PI。

Anti-windup, Kaw—Gain
`1`(default) |`scalar`

Anti-windup gain,K_aw, dimensionless.

Dependencies

To create this parameter, setControl typetoPIorScheduled PI。

Error filter time constant, tauerr—Filter
`。01`(default) |`scalar`

Error filter time constant,τ_err, in s. To disable the filter, enter 0.

Dependencies

To create this parameter, setControl typetoPIorScheduled PI。

Predictive