The slide contains the simulation of pneumatic active suspension behavior on different road surface. These results shows the active suspension with controllers works effectively,if feedback loop is provided.

1. Tushar Tambe
Reg. No:16MMT1034
M.Tech, SMBS, VIT
University,Chennai Campus
Design and Development of Vehicle
Active Suspension System Using
PID Controller
1
Under the supervision of
Dr.Saravanakumar D
SMBS, VIT University ,Chennai Campus

2. Introduction
A vehicle suspension system is a complex vibration system having multiple degrees of
freedom . The purpose of the suspension system is to isolate the vehicle body from the
road inputs.
 Suspension systems serve a dual purpose
Contributes to vehicle's
road handling and
braking for safety and
driving pleasure.
Cornering Braking
 Suspension should be soft against road disturbance and hard against load disturbance
Active suspension can provide better cornering and braking due to reduction in weight
transfer.
2

3. Motivation
3
Study of Suspension system aims at benefitting :
1. Ride stability of Vehicle
2. Ride Comfort for Passenger
3. Long Life of Vehicle

4. Parameters Passive Active
Regulator element General shock-
absorber
Hydraulic or
pneumatic or general
Action Principle Damping constant Adjust force between
wheel and vehicle
body
Control No Electronic
Dynamic
Characteristic
No High
Cost Low High
Energy consumption No Yes
Comparison
4
Courtesy: Vehicle Dynamics- IIT-H

5. Literature Review
PAPER STUDY
1. Y. M. Sam, M. R. Ab.Ghani, and N.
Ahmad. “LQR Controller For Active Car
Suspension”. Mechanical Journal of Control
and instrumentation. 2000, pp.I-441-I-444
An active suspension increased a tire to
road contact in order to make the vehicle
more stable.
It also provides better ride comfort and
ride handling
2. A .Kruczek and J. Honcu. “Active
Suspension-Case study on Robust
Control”. World Academy of Science,
Engineering and Technology, 2011
Active Suspension’s riding comfort and
handling can also be controlled by H-
infinity controllers.
3. Ahmed Elmarakbi, Chandrasekaran
Rengaraj, Alan Wheatley & Mustafa Elkady.
“The Influence of Electronic Stability
Control, Active Suspension, Driveline and
Front Steering Integrated System on the
Vehicle Ride and Handling”. Global
Journal of Researches in automotive
engineering,2013
Intelligent controllers such as fuzzy logic
have been implemented into the active
system.
This improves riding comfort of vehicle.
5

6. Literature Review
PAPER STUDY
4.Faraz Ahmed Ansari, Rajshree Taparia ,
“Modeling, Analysis and Control of Active
Suspension System using Sliding Mode
Control and Disturbance Observer” 2009
5th International Colloquium on Signal
Processing & Its Applications (CSPA)
Sliding control mode was implemented to
control vehicle stability
5.Andrew Alleyne and J. Karl Hedrick
“Nonlinear Adaptive Control of Active
Suspensions” IEEE transactions on control
systems technology, vol.1, no.1.march1995
A nonlinear sliding control law is applied
to an electro-hydraulic suspension system
6. M. Senthil, “Development of Active
Suspension System for Automobiles using
PID Controller,” vol. II, 2008
PID controller were used to stabilize the
vehicle by using step and sinusoidal using
transfer fuction.
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7. Objectives
To develop PID control suspension system, which can
adapt to road roughness values.
To achieve
1. Stability of ride (Handling of car)
2. Passenger comfort.
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8. 1
• Developing Mathematical Model for Passive and Active Suspension
System
2
• Parametric determination of constant
3
• Actuator modeling
4
• Selection of Road inputs
5
• Implementation of mathematical modeling in Matlab/Simulink.
Methodology
8

9. Mathematical modeling(Passive System)
Passive Suspension System:
It is ordinary spring-damper
arrangement with constant spring
coefficient and damping coefficient
Notations Used:
Ms: Sprung Mass, Kg
Mus: Unsprung Mass, Kg
K1: Spring Stiffness, N/m
K2: Tire Stiffness, N/m
Ca: Damping coefficient, Ns/m
Xs: Vertical Sprung mass displacement, m
Xus: Vertical Unsprung mass displacement, m
Xr: Vertical road profile displacement, m
F: Force generated by actuator,N
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For sprung mass:
Ms Xs + Ca (Xs - Xus) + K1 (Xs - Xus) =0 …. (1)
For unsprung mass:
Mus Xus + Ca (Xus -Xs) + K1 (Xus - Xs) + K2 (Xus – Xr) =0 .... (2)

10. Mathematical modeling(Active System)
For sprung mass:
Ms Xs + Ca (Xs - Xus) + K1 (Xs - Xus) = Fa
For unsprung mass:
Mus Xus + Ca (Xus -Xs) + K1 (Xus - Xs) + K2 (Xus – Xr) = -Fa
Here,
Fa = A1P1 – A2P2
Active Suspension System:
Fa : Actuator Force
A1: Area on piston
side
A2: Area on Piston rod
side
P1: Pressure on piston
side
P2: Pressure on Piston
rod side
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11. Parameter Value
Sprung mass
(Ms )
250 kg
Unsprung mass
(Mus )
50 kg
Spring stiffness
(K1 )
18,600 N/m
Damping coefficient
(Ca )
1,000 Ns/m
Tire stiffness
(K2 )
196,000 N/m
Parametric Constant(1/4 Vehicle model)
Parameter Value
Area on piston side
(A1, D=50mm)
1.963µm2
Area on Piston rod
side (A2,d=10mm)
1.256µm2
Orifice area of spool
(ac , d=1mm)
3.14µm2
Adiabatic Index (K) 1.4
Length of Actuator
(l)
150mm
Suspension Data : Actuator Assumed Data :
11

12. Actuator Modeling
Actuator Mathematical Modeling
Notations Used:
Ms: Sprung Mass, Kg
Mus: Unsprung Mass, Kg
Mi: Mass Flow Rate, kg/s
Pi: Chamber Pressure, N/m2
Ca: Damping coefficient, Ns/m
Xa: Actuator displacement, m
Xr: Vertical road profile displacement, m
Fa: Force generated by actuator, N
R : Gas constant
V : Voltage, V
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- -

13. Actuator Simulink Model
13

14. Matlab Simulink Model (Passive System)
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15. Matlab Simulink Model (Active System)
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16. Road Input Signals
Step Input Sine Input
White Noise Input
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17. White Noise Road Input Signal
q(t) - Random road input signal;
- Filter lower-cut-off frequency;
- Road roughness coefficient,
w(t) - Gaussian white noise.
Random road input signal Road Level
A 16
B 64
C 256
D 1024
E 4096
F 16384
G 65536
H 262144
ISO 8608: Road Classification
According to
Actual White Noise Input
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18. Simulation For Step Input
Unsprung mass acceleration Vs Time
Sprung mass acceleration Vs Time
Unsprung mass Displacement Vs Time
Sprung mass Displacement Vs Time
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19. Simulation For Sine Input
Unsprung mass acceleration Vs Time
Sprung mass acceleration Vs Time
Unsprung mass Displacement Vs Time
Sprung mass Displacement Vs Time
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20. Simulation For White Noise Input
Unsprung mass acceleration Vs Time
Sprung mass acceleration Vs Time
Unsprung mass Displacement Vs Time
Sprung mass Displacement Vs Time
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21. Parameters
Overshoot Values
%ReductionPassive Active
Sprung mass
Displacement(m)
1.4593 0.2914 80.035
Sprung mass
Acceleration(m/s2)
18.4306 3.6950 79.95
Unsprung mass
Displacement(m)
1.5018 0.3005 79.99
Unsprung mass
Acceleration(m/s2)
22.2859 3.4500 84.51
Parameters
Peak Values
%ReductionPassive Active
Sprung mass
Displacement(m)
1.0781 0.2316 78.51
Sprung mass
Acceleration(m/s2)
23.650 11.84 49.93
Unsprung mass
Displacement(m)
1.0407 0.4066 60.93
Unsprung mass
Acceleration(m/s2)
25.144 13.50 52.58
Parameters
Peak Values
%ReductionPassive Active
Sprung mass
Displacement(m)
0.00624 0.00134 78.52
Sprung mass
Acceleration(m/s2)
0.0312 0.00632 79.74
Unsprung mass
Displacement(m)
0.00621 0.00134 78.42
Unsprung mass
Acceleration(m/s2)
0.0343 0.00634 81.51
STEP INPUT SINE INPUT
WHITE NOISE INPUT
Results
0
10
20
30
40
50
60
70
80
90
Sprung mass
Displacement
Sprung mass
Acceleration
Unsprung
mass
Displacement
Unsprung
mass
Acceleration
STEP INPUT SINE INPUT WHITE NOISE INPUT
REDUCTION IN PEAK VALUES
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22. Conclusion
 The various observations made during the project clearly indicate that
the preference priority level for suspensions is
1: Active suspension
2:Passive suspension
 The results also indicated that a stability system is also required for
better overall performance of the vehicle.
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23. Future Work
Improvement of the suspension system considering the
experience of real world
 Consider the dynamic behavior of suspension system and
tire deflection execution through fitting change.
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