Project 2 Adaptive Cruise Control

Aim: To develop an MBD-compliant Adaptive Cruise Control feature as per the provided requirement document using MATLAB Simulink.

Objectives:

1. To develop logic and create a Simulink model of ACC as per the Requirement data.

2. Create a data dictionary and link it to the model.

3. To generate Model advisor reports and code generation.

Steps to model the Adaptive cruise control algorithm:

1)Creating a Simulink model of the ACC algorithm

• Three subsystems are created for the three provided requirements namely Lead_Vehicle, Drive_Vehicle, and ACCAlgorithm

Lead_Vehicle subsystem: The camera and radar inputs values are taken as inputs and Lead vehicle speed will be the output as specified in requirement1

Drive vehicle subsystem: This block follows the conditions of Requirement2 and takes 3 input values for Camera input, radar input, and acceleration mode. There will be 2 outputs of drive vehicle speed and lead vehicle detection signal.

ACC algorithm subsystem: This subsystem is developed on Requirement 3 and is made using the concept of Stateflow. It takes 8 inputs and gives the acceleration mode as the final output.

ACC Algorithm Stateflow diagram: The Stateflow chart is developed based on the 6 sub-requirements specified in Requirement 3.

• The adaptive Cruise Control feature has 3 major modes of operation: OFF Mode, STANDBY Mode & ON Mode. This particular requirement has to be implemented as state machine logic in Simulink.
• The input signals to this state machine system are (Signal Name: Time_Gap, Set_Speed, Set_Gap, CruiseSwitch, SetSwitch).
• Also, the output signals (Signal Name: DriveVehicle_Speed & LeadVehicle_Detected) from requirement-2 are fed back as an input signal into this state machine block.
• Additionally, the output signal (Signal Name: LeadVehicle_Speed) from requirement-1 is given as an input signal to this state machine block as well.
• Output from this subsystem is a signal (Signal Name: Acceleration_Mode) which governs the vehicular speed of the drive vehicle which automatically adjusts its speed & velocity to match the lead vehicle.

Statlow symbol pane:

3) Signal resolving and propagation

• Name the imports and signals by method of signal resolving and propagation.
• A signal is resolved when it appears for the first time and the signal is then propagated then onwards
• Signal to resolve: Right Click on the signal > properties > enter a valid signal name and click on the SLDD suggestion > check the resolve signal box > OK
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• Signal propagation: Double-click on the signal, add <>, and press enter.
• Or Click on the signal > properties > Check the "Show propagated signal" option > OK
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• The resolved signal will be propagated
• Avoid signal overlapping by using the goto and from blocks

4) Requirement tagging

• Require tagging is the process of linking the model with a document or a file that explains the model requirements by just clicking on the name
• The Word document with requirement details is opened.
• Select the heading and highlight it.
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• Right Click on the subsystem that explains the highlighted portion > requirements > Link to selection in word
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• We can now see in the requirement section that the subsystem is linked to the word document.
• If anyone clicks on the requirement tag, the Word document containing its details will be opened.

5) Configuration of Solver settings and Code generation

• Go to model settings > Solver > select type: Fixed step ; solver: discrete (no continuous states) ;Fixed step size:0.01 > OK
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• Go to code generation > system target file: select ert.tlc >OK
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6) Model advisor check

• Model advisor checks are done to check compliance of the model with different guidelines
• Run the model and check for any errors
• If the model is error-free, we can proceed with the advisor check
• Here we are just performing the model advisor check on MAB standards
• Go to model advisor > select the whole system >OK
• Model advisor > select "By task"
• Select "modeling standards for MAB"
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• Click on generate report. The file name and the location where the generated file will be stored are displayed there
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• Once the report is generated, the advisor results can be seen with the total number of the pass, fail, warnings, and tasks.
• The errors must be eliminated to 0 numbers
• The warnings must be reduced to a minimum.
• To correct a warning, select the folder for which the warning is shown > select the subfolder with the warning sign > The warning parameters and correction methods as shown here
• Follow the correction recommendation and click OK when done correcting
• Now the warning number can be seen reduced.

7) Code generation:

• Once the warnings are reduced to the maximum, we can generate a C code for the model created
• Go to model explorer > open requirement 2 > set the parameters
• Go to APPS tab > Embedded Coder > Select the model name >Gerate code /Build
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• The code will be displayed and it's also saved in the selected directory.
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Simulink blocks used:

• Subsystem
• Add block
• Signal conversion
• Chart
• In-port and outports
• Unit Delay

Procedure:

As per the Requirement document, implemented the Adaptive Cruise Control feature.

Lead vehicle:

• To detect the lead vehicle speed, simply added both the radar & camera inputs & the corresponding output is read as Speed profile output.

Drive Vehicle:

• To regulate the "Drive Vehicle speed", as per the Requirement document added CameraInput, RadarInput & Acceleration_Mode feedback from ACC Algorithm.
• To detect the Lead vehicle, RadarInput is converted using a "Signal Conversion Block".
• To avoid the algebraic error "Unit delay" block is used for the Acceleration_Mode feedback.

ACC Algorithm:

• The adaptive Cruise Control feature has 3 major modes of operation: OFF Mode, STANDBY Mode & ON Mode. This particular requirement has to be implemented as state machine logic in Simulink.
• The input signals to this state machine system are (Signal Name: Time_Gap, Set_Speed, Set_Gap, CruiseSwitch, SetSwitch).
• Also, the output signals (Signal Name: DriveVehicle_Speed & LeadVehicle_Detected) from requirement-2 are fed back as an input signal into this state machine block.
• Additionally, the output signal (Signal Name: LeadVehicle_Speed) from requirement-1 is given as an input signal to this state machine block as well.
• Output from this subsystem is a signal (Signal Name: Acceleration_Mode) which governs the vehicular speed of the drive vehicle which automatically adjusts its speed & velocity to match the lead vehicle.
• The rest of the algorithm is developed as per the Requirement.

Result:

• The adaptive cruise control is modeled in Simulink as per the given requirements and MBD guidlines
• Performed requirement tagging on the requirement subsystem blocks
• Solver and code generators are configured
• SLDD file is created and linked to the model also the signals are resolved and propagated
• Model advisor report is generated and verified
• The c-code for the model is generated and attached

The Simulink model, the model Word document, the SLDD file , and the advisor report are attached in the form of a zip file below