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ENEM20001 Application Of Mechanical Control
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ENEM20001 Application Of Mechanical Control
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Course Code: ENEM20001
University: Central Queensland University
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Country: Australia
Question:
Problem Investigation, Scope, Assumptions and Limitations State and justify the assumptions you make of the Quad bike’s engine and drivetrain performance. (i.e. maximum torque, power, gear ratios)
Revisit your Project 1 results and state the starting suspension properties, payload details and variations you will consider for the project (i.e. stiffness and damping values, rider mass, payload mass, location, mass variations, and road variations). Use these variations in each of the following analysis where appropriate.
State any limitations and analysis your report does not cover but could have been done if a larger analysis was required and more time and information was available. You may need tocheck and add to this section at the end of the project.
Your analysis will include the points below. Explain your working and models so an engineer could understand your process, results and findings of each point. Use each analysis point to help in the main aim described in Section 2.0.
Draw a mathematical model schematic of the quad bike with traction provided by the engine.
Simplify the system to a single degree of freedom system (horizontal motion only).
Draw the horizontal 1 DOF free body diagram and write the modelling equation. Also add in wind drag and other frictional forces to make your model more realistic. State any external references to justify your assumptions.
Model the system in Simulink to determine the acceleration/speed/position vs time of the quad bike at various throttle positions.
Compare the Simulink results with some theoretical calculations to check your model.
In a conclusion to Part B, discuss how your simplified model may differ from the real system (i.e. wheel-road friction limits, tire stiffness, engine power and torque curves etc.). Discuss how you might improve the accuracy of your horizontal model further.
Complete the following points in regards to the whole project:
Discuss how you would model the quad bike as a four degree of freedom system by modelling the mass of the wheels. Also show the schematic and FBD’s you would use.
Also discuss what benefits this may provide in relation to both dynamic analysis and accuracy of the controller.
State your final design for the quad bike suspension stiffness, damper values and recommendations for a controller.
Comment on if your controller was a success and what changes you recommend to the controller to improve it if you had more time.
Discuss the steps you would take to implement the controller on a real quad bike.
Summarise your key findings and observations from the whole project.
Answer:
Problem Statement & Scope
The aim of the project is to progress or design a drive-line control for the quad bike. The controller seeks to reduce misfortunes and produce consistent stunts while it is anticipated to have a mechanized control of the wheel stand disarray. The controller tests the operation of the second degree of freedom of the quad bike using a rotational and translational model of the Simulink designed in the prior analysis.
Limitations
The project focuses on the second degree of freedom only for the analysis of the quad bikes drive train performance and engine operation in terms of maximum torque, power, and gear ratios.
Assumptions
This is the all-terrain version of Quad bike that operates on the basis of vehicle propagation for translational and rotary motion. The gravitational acceleration is given as 9.81 ms-2.
The quad bike has a single rider at every analysis. The chassis and the wheels constitute the entire weight of the quad bike.
Road surface is uniform throughout the analysis.
Horizontal Speed And Position Model
B1 Mathematical model schematic of the quad bike with traction provided by the engine
B2: Simplify to a single degree of freedom system (Horizontal motion only)
B3: Draw the horizontal 1 DOF free body diagram and write the modelling equation.
B4: Model the system in Simulink to determine the acceleration, speed, position vs time of the quad bike at various throttle positions.
B5: Simulink results are compared with theoretical computations of the model.
B6: conclusive discussion
There is a lag before rise time. This could mean that the quad bike takes some time before it accelerates to certain speeds. Such an engine performance is undesirable hence there is need for better control measures that will monitor the operation of the system and reduce the rise time as well as the overshoot.
Two Degree Of Freedom Model With Controller (Vertical And Pitch)
C1: Estimation the center of gravity location of the rider and payload variations.
Payload variations
Parameter
Value
Rider mass
67 kg (670N)
Payload mass
3140 kg (31400N)
Location
Adelaide, Australia
Mass variations
45-56 kg
Road variations
6m ~0.02 m
C1- suspension spring stiffness
25000 (N/m)
B1- suspension absorber damping
1000 (Ns/m)
C2- front axle bellows stiffness
300,000 (N/m)
C.2 Draw the simplified model schematic and the 2 DOF FBD and write the modeling equations
C3 creating a suitable 2DOF simulink model.
C.4 Adding a feedback loop of PID controller to the model to achieve a wheel stand on level ground
C.5 Determining the engine or drive train forces and wheel-road friction levels required for the different controllers and the assumed maximum capacities of the engine and wheel-road surface.
The engine or drive train forces, wheel road friction levels, the different controllers as well as the assumed maximum capacities of the engine and wheel-road surfaces.
Further Model Improvements
D1: Add limitations of engine power or torque and the wheel-road interface to the model. Update controller to accommodate the limitations.
The limitations added to the system are in form of white Gaussian noise. It represents fault engine with lower performance.
D2: combine the output with the system output of the horizontal model in part B
D3: Analyze the performance of the controller based on the road corrugations, defects, and variations in payload and positioning.
Determining the static tire deflection while in contact with the road corrugated surface,
Neglecting the air resistance, the wheels encounter the surface and develop a trajectory whose path is defined as,
When analyzing the system on a horizontal plane, the vertical reactive forces that act on the tire keep changing which affects the rolling radius. It is also important to consider the slippage which is defined as,
Which defines effective rolling radius and the static rolling radius.
The Bekker equation shows that the relationship between the horizontal and the vertical loads are based on the corresponding deformations and could be expressed by,
D4: re-assess the quad bike spring and damper values based on the chosen values in prospect 1.
The values chosen for the Quad bike Spring and damper in the first analysis were
For the case with a PID controller, the system stabilizes at a short duration. The system is able to develop consistency and access to the system parameters and it deflects the noises in its environment.
The values are approximately ten times lower than those of the previous system.
D5: Analyze the stability of the final model and controller
Stability of a system is determined using the root locus plot to observe the position of the poles.
D6: key findings and observations.
A controller stabilizes the system in the presence of noise, either white Gaussian noise or the translational noise from the road surfaces.
Conclusion
E.1 Consider a Quad bike as a four degree of freedom system by modeling the mass of the wheels. The modeling of the masses to a four degree of freedom.
A degree of freedom is the scope of movement an entity has in any one particular direction. For instance, an arm with four degrees of freedom can have motion in two axial directions; say along the x-axis and along with y-axis.
E2 Benefits in relation to both dynamic analysis and accuracy of the controller
Controller is able to ensure that only the anticipated yield is obtained at the output despite the system errors that may arise.
E3 Final design for the quad bike suspension stiffness, damper values and recommendations for a controller.
Design for quad bike suspension stiffness, damper values, and recommendations
spring coefficient = 30,000 N/m
Damping coefficient = 2950 Ns/m
The controller gain parameters for the PID controller were adjusted throughout the testing phase as shown in the table below,
Parameter
Test 1
Test 2
Test 3
Test 4
Test 5
Kp
650
750
1000
1250
850
Kd
15
35
10
20
25
Ki
4500
4800
4000
3500
5000
Recommendations for the controller.
The controller should be embedded on a chip and installed in the electrical connection point in the quad bike. At that point, it can control the system and ensure that that quad bike deals with rough terrain as well as abnormalities during the drive train. In modern era, the use of artificial intelligence fuzzy technique is quite prevalent. The fuzzy systems monitor a systems operations and determines certain patterns in the system. Such patterns can provide additional information to the controller to improve its performance.
E4. Discuss about the controller.
The proportional controller is used in the first order systems. It manipulates a proportional gain constant which is used to alter the value of the output. The gain parameter is multiplied with the system first order system to give a new yield to the system. The gain parameter minimizes the steady state error but it does not eliminate the errors. The gain parameter is denoted as, Kp. Adjusting the value increasingly minimizes the steady state error. The value may be increased to a given value which is consider the optimum value which results in a reduced amplitude and phase margin. Exceeding the value may cause the output to oscillate during dead time or lag. The proportional-integral controller, on the other hand, eliminates the steady state error completely. The control parameters are denoted as Kp and Ki.
The controller is implemented in areas where speed is not a performance factor. Unfortunately, the controller is not able to predict future errors in the system and it can neither reduce the rise time nor eliminate the oscillations that may result when the value of the proportional gain parameter is very high. The PID controller solves the issues that other controllers are unable to solve. It guarantees optimum control dynamics to obtain zero steady state error, faster response which implies a shorter rise time, no oscillations, no overshoots, and higher stability. The controller can be implemented in systems of higher orders unlike the proportional controller which is limited to first order systems only.
E5 Steps to implement the controller on a real quad bike
Determine the electrical connection section of the system.
Study the integration of the electrical part of the Quad Bike with the wheel system at the axle and the engine. At the point of connection, embed the controller.
The best method to embed the controller is done using PLC, PIC or an Arduino-programmed chip which is programmed and inserted on the device.
Tests are carried out to ensure that the system functions as expected. The feedback loop collect information from the environmental noise and incorrect yields, processes the error and makes adjustments to ensure that the system performs as it is intended to.
E6 summarize the key findings and observations
Operating a system as an open loop exposes it to a lot of external and internal disturbances which in turn affect the system’s performance. The system’s performance is given on the basis where the system output reflects the intended system output.
References
A.G. Keskar. “Robotic Arm with Four Degrees of Freedom” , 2008 First International Conference on Emerging Trends in Engineering and Technology, 07/2008.
Kerchmann, V. & Hohman, R. E. T., 2009. Dynamic tire friction models for Quad Bikes Traction control. Decision and Control: Proceedings of the 38th IEEE conference, 13(4), pp. 3746-3751.
Seoung-On, K. et al., 2012. Actively translating a rear diffuser device for the aerodynamic drag reduction of a passenger car. International l Journal of Automotive Technology, 13(4), pp. 583-5
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