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TRANSCRIPT
Firma convenzione Politecnico di Milano e Veneranda Fabbrica
del Duomo di MilanoAula Magna – Rettorato
Mercoledì 27 maggio 2015
MeccPhD Evaluation
Alireza Izadi
Cycle XXVIII Dynamics and Vibration of Mechanical Systems and Vehicle
Thesis Title: Active roll control of an articulated heavy vehicle using
the existing air suspension
Supervisors: Prof. Edoardo Sabbioni/Prof. Federico CheliTutor: Prof. Massimiliano Gobbi
Alireza Izadi, MeccPhD, Three and a half year Evaluation 2/32
Contents
1. Introduction2. Methodological approach3. Vehicle Modeling4. Control Logics design5. Actuators Modeling6. Results
– Comparison of different control logics– Comparison of actuators– Active tractor and active trailer– Robustness
7. Conclusion8. Doctoral curriculum
Alireza Izadi, MeccPhD, Three and a half year Evaluation 3/32
Problem and solutions
The problem:• 35 % of fatal accidents caused by HVs• Rollover causes 38% of fatal accidents in HVs
and it is the most horrible accident.
Preventability of rollover accidents:• 50% are impossible to control even with
professional drivers.
Solution:• Active roll control is the most strong solution
for rollover accidents
Fig 1. Preventability of rollover accidents by driver.
Fig 2. Passive roll control vs. active anti‐roll control application.
3.3
38.4
49.7
8.6
0
10
20
30
40
50
60
Possible Maybe Impossible unknown
Problem and solutions
Aim of work, main features, and innovative aspects
Methodological approach Vehicle models Control logics Actuators Results Conclusion
(a) (b)
Alireza Izadi, MeccPhD, Three and a half year Evaluation 4/32
Aim of the work, main features and innovative aspects
Aim of the work:is to develope a rollover controller to tilt the vehicle toward the inside of turn to minimize lateral load transfer.
2. Main features: appropriate improvement with robust operation to different payloads and velocities, proper energy consumption, flow rate and bandwidth of actuators, low installation and operational costs
In comparison with the state of the art considering Control logics Actuators (active anti roll bars)
3. Innovative aspects: o Using the full potential of existing air springs for roll control design,o Designing the control logic based on:
o minimum measurements, o precise and low cost estimations and o an optimal load distribution on the axles.
Problem and solutions Aim of work, main features, and innovative aspects
Methodological approach Vehicle models Control logics Actuators Results Conclusion
Alireza Izadi, MeccPhD, Three and a half year Evaluation 5/32
Methodological approach
Fig 3. Methodological approach for active air suspension design.
Problem and solutions Aim of work, main features, and innovative aspects
Methodological approach Vehicle models Control logics Actuators Results Conclusion
1. Vehicle Modeling 2. Control Design 3. Actuator Modeling
A. Multibody VM
B. 9‐DoF VM
C. 5‐DoF roll‐plane VM
D. Logic 1
E. Logic 2
F. Logic 3
G. Active anti‐roll bars
H. Active air springs
A. Multibody VMActuatorsControl
Logic+‐ /x
4. System integration
Mod
eling
System
integration
5.The best compromise for rollover controllerResult
Alireza Izadi, MeccPhD, Three and a half year Evaluation 6/32
Active Roll control design process
1. Introduction2. Methodological approach3. Vehicle Modeling4. Control Logics design5. Actuators Modeling6. Results
– Comparison of different control logics– Comparison of actuators– Active tractor and active trailer– Robustness
7. Conclusion
Alireza Izadi, MeccPhD, Three and a half year Evaluation 7/32
1. Nonlinear multibody vehicle model
A complicated nonlinear vehicle modelincludes:
• 192 ordinary differential equations,• 76 bodies,• 30 multibody degrees of freedom• 73 multibody coordinates,• Nonlinearities Jounce and rebounds bump stops 5th wheel roll, pitch and yaw bumps Spring hysteresis Tire deflection
Problem and solutions Aim of work, main features, and innovative aspects
Methodological approach Vehicle models Control logics Actuators Results Conclusion
The multibody model is used for co‐simulating with Simulink to:1. validate the simplified linear vehicle models and 2. describe the response of the tractor semitrailer.
Fig 4. Visualization of nonlinear multibody vehicle model.
Alireza Izadi, MeccPhD, Three and a half year Evaluation 8/32
2. Linear models
‐ Simplified 9‐DoF vehicle model: ‐ Simplified 5‐DoF vehicle model:
9‐DoF tractor semitrailer model. ∅ ∅
∅ ∅ ∅
∅ ∅ ∅ ∅ ∅ ∅ ∅ ∅ ∅ ∅
Fig 5. 9‐DoF tractor semitrailer model and states is used in the full state and partial state feedback controllers.
Fig 6. 5‐DoF roll plane model and states is used in reduced order controller design.
Problem and solutions Aim of work, main features, and innovative aspects
Methodological approach Vehicle models Control logics Actuators Results Conclusion
This model is used for designing our full state feedback controller.
This model is applied for designing our minimum order controller.
Validated by Nonlinear Multibody Model
∅ ∅ ∅ ∅ ∅ ∅ ∅
Alireza Izadi, MeccPhD, Three and a half year Evaluation 9/32
Comparison of linear and nonlinear vehicle model
Fig 7. Trajectory of tractor semitrailer.
Fig 12. load transfer on wheels.
Fig 11. Suspension roll angle. Fig 8. Yaw angle of tractor semitrailer.
Fig 9. Yaw rate of tractor semitrailer. Fig 10. Lateral acceleration of tractor semitrailer.
Problem and solutions Aim of work, main features, and innovative aspects
Methodological approach Vehicle models Control logics Actuators Results Conclusion
Alireza Izadi, MeccPhD, Three and a half year Evaluation 10/32
Active Roll control design process
1. Introduction2. Methodological approach3. Vehicle Modeling4. Control Logics design5. Actuators Modeling6. Results
– Comparison of different control logics– Comparison of actuators– Active tractor and active trailer– Robustness
7. Conclusion
Alireza Izadi, MeccPhD, Three and a half year Evaluation 11/32
Control logics
Control objective of all controllers:• Reducing the load transfer by tilting the vehicle towards the turn.
Control logics:Logic 1: Proportional lateral acceleration feedback controlLogic 2: Full-State feedback controlLogic 3: Optimal minimum order control
Selection criteria:• The controllers response in transient and steady state condition(reliability),• Robustness• Number of measurements • Estimation precision and costs• implementability
Problem and solutions Aim of work, main features, and innovative aspects
Methodological approach Vehicle models Control logics Actuators Results Conclusion
Alireza Izadi, MeccPhD, Three and a half year Evaluation 12/32
Logic 1: Proportional lateral acceleration feedback
PD Controller
PD Controller
ActuatorsActuators Multi‐body Vehicle
Multi‐body Vehicle
,
Fig 13. Proportional lateral acceleration feedback control logic.
LOGIC 1 (Specifications): 1. The simplest controller includes only a proportional gain.2. Minimum number of measurements.
Problem and solutions Aim of work, main features, and innovative aspects
Methodological approach Vehicle models Control logics Actuators Results Conclusion
Gain selection :The control law is:
.The proportional gain is tuned to have a proper suspension roll angle in oppositedirection of the roll moment caused by the lateral acceleration.
Alireza Izadi, MeccPhD, Three and a half year Evaluation 13/32
Logic 2: Full-state feedback controller (LQR)
LOGIC 2 (Specifications):1. It is a multivariable optimal controller with disturbance rejection properties.2. It needs the highest number of measurements among the controllers.
Problem and solutions Aim of work, main features, and innovative aspects
Methodological approach Vehicle models Control logics Actuators Results Conclusion
Linear Quadratic Regulator Actuation System
,
Control technique:To use the linear quadratic optimization to regulate the load transfer in the presence of steering disturbance.
∅ ∅ ∅ ∅ ∅
Fig 14. State feedback control logic algorithm.
Alireza Izadi, MeccPhD, Three and a half year Evaluation 14/32
Logic 2: Full-state feedback controller (LQR)
Control gain matrix calculation :1. Considering the linear dynamic system:
2. Control problem:The control minimizes the quadratic performance index:
Q : the relative weighting of the performance output xR : the weighting matrix of control input u(t).
3. Optimal control law:
Where
Problem and solutions Aim of work, main features, and innovative aspects
Methodological approach Vehicle models Control logics Actuators Results Conclusion
, Eqn. 1
x x Eqn. 2
x δ Eqn. 3
S is the unique solution of algebraic Riccati formula.
Linear Quadratic Regulator Actuation System
,
Alireza Izadi, MeccPhD, Three and a half year Evaluation 15/32
Disadvantages of logic 2:1. It requires all the internal states of the system and all the disturbance
states available for feedback,2. difficult and expensive to measure states,3. the sensor output signals are corrupted by noise.
Logic 2: Full-state feedback controller (LQR)
Problem and solutions Aim of work, main features, and innovative aspects
Methodological approach Vehicle models Control logics Actuators Results Conclusion
A practical proposition is:• to measure selected vehicle states• Estimate the unmeasured states• Filter measurement noise
1. An optimal controller with minimum measurements and proper estimations2. Reasonable estimation cost
Logic 3: An optimal minimum order controller
Alireza Izadi, MeccPhD, Three and a half year Evaluation 16/32
The minimum order controller consists 1. A state estimator 2. An optimal controller
Logic 3: Optimal minimum order controller
Fig 15. The designed minimum order controller.
ActuatorsForce control MB Vehicle
,,
State Estimator
LQR
, ∆∅ ∅ ∅ ∅ ∅ ∅ ∅ ∅ ∅ ∅
Problem and solutions Aim of work, main features, and innovative aspects
Methodological approach Vehicle models Control logics Actuators Results Conclusion
MeasurementsSpeed Steer angle Lateral acceleration Air springs elongation Air spring pressure
Table 1. Measurements of minimum order controller.
The estimations are in a very good agreement with measurements.√
Alireza Izadi, MeccPhD, Three and a half year Evaluation 17/32
Active Roll control design process
1. Introduction2. Methodological approach3. Vehicle Modeling4. Control Logics design5. Actuators Modeling6. Results
– Comparison of different control logics– Comparison of actuators– Active tractor and active trailer– Robustness
7. Conclusion
Alireza Izadi, MeccPhD, Three and a half year Evaluation 18/32
Actuators
.
Fig 16. ARB system configuration (SATA). Fig 17. Air springs configuration.
1. Active anti-roll bars 2. Active air springs
Problem and solutions Aim of work, main features, and innovative aspects
Methodological approach Vehicle models Control logics Actuators Results Conclusion
Two actuator models were developed:1. Active anti‐roll bars with 4 Hz bandwidth2. Active air springs with 2 Hz bandwidth
Alireza Izadi, MeccPhD, Three and a half year Evaluation 19/32
Active air springs configuration
Axle Bandwidth L1 (mm) L2 (mm) Load reduction (%)
Steer
2 Hz‐ ‐ 20
Drive 500 500 50
Trailer 500 480 46
Problem and solutions Aim of work, main features, and innovative aspects
Methodological approach Vehicle models Control logics Actuators Results Conclusion
Steer axle Drive axle Trailer axles
Table 2: BPW 360K‐1 air springs with 360 mm diameter.
Fig 18. Air springs configuration on steer axle (a), drive axle (b) and trailer axle (c).
(a) (b) (c)
Fig 19. air spring installation on trailer axle.
Alireza Izadi, MeccPhD, Three and a half year Evaluation 20/32
Active Roll control design process
1. Introduction2. Methodological approach3. Vehicle Modeling4. Control Logics design5. Actuators Modeling6. Results
– Comparison of different control logics– Comparison of actuators– Active tractor and active trailer– Robustness
7. Conclusion
Alireza Izadi, MeccPhD, Three and a half year Evaluation 21/32
Suspension response by using controllers - Ramp steering (steady state maneuver, 60 km/h)
1. The controllers have small and acceptable deviations, thus they have satisfactoryresponse for active air springs system.
2. Suspension tilts inward the turn to reach the maximum capacity of air springs andthen it tilts backward.
3. All in all, there is a considerable improvement in rollover threshold.
Fig 21. Normalized load transfer vs. lateral acceleration. Fig 22. Suspension roll angle vs. lateral acceleration.
Comparison of ControllersActive air springs
Actuators capability
Actuators comparison
Active combinations and 5th wheel study Robustness AnalysisRESULTS:RESULTS:
Alireza Izadi, MeccPhD, Three and a half year Evaluation 22/32
Suspension response by using controllers - Double lane change steering (Transient maneuver, 60 km/h)
• In DLC the optimal controllers are performing very good.• The response of optimal controllers are better than proportional lateral acceleration
feedback controller which causes higher improvement for them.
Fig 23. Normalized load transfer vs. lateral acceleration. Fig 24. Suspension roll angle vs. lateral acceleration.
Comparison of ControllersActive air springs
Actuators capability
Actuators comparison
Active combinations and 5th wheel study Robustness AnalysisRESULTS:RESULTS:
Alireza Izadi, MeccPhD, Three and a half year Evaluation 23/32
Controller selection
The minimum order control logic is the most appropriate control logic for the roll control purpose.
Comparison of ControllersActive air springs
Actuators capability
Actuators comparison
Active combinations and 5th wheel study Robustness AnalysisRESULTS:RESULTS:
Specifications of control logic 3• low number of measurements,• reasonable estimation cost,• very good response in steady state and transient condition,• with disturbance rejection properties.
Alireza Izadi, MeccPhD, Three and a half year Evaluation 24/32
Active Roll control design process
1. Introduction2. Methodological approach3. Vehicle Modeling4. Control Logics design5. Actuators Modeling6. Results
– Comparison of different control logics– Comparison of actuators– Active tractor and active trailer– Robustness
7. Conclusion
Alireza Izadi, MeccPhD, Three and a half year Evaluation 25/32
Actuators comparison- Ramp steering (steady state maneuver, 60 km/h, )
Maximum Improvement Active anti‐roll bars Active air springs
Normalized load transfer (%) 16.81 9.81
Rollover threshold (%) 17.99 7.64
Comparison of ControllersActive air springs
Actuators capability
Actuators comparison
Active combinations and 5th wheel study Robustness AnalysisRESULTS:RESULTS:
Table 4. Normalized load transfer and rollover threshold improvements.
Fig 25. Active and passive normalized load transfer for active anti‐roll bars (a) and active air springs (b).
Active anti‐roll bars Active air springs
Although active anti‐roll bars have higher capabilities, air springs have a considerable improvement within their potentials.
(a) (b)
Active anti‐roll bars Active air springs
17.99 7.64
Alireza Izadi, MeccPhD, Three and a half year Evaluation 26/32
Active Roll control design process
1. Introduction2. Methodological approach3. Vehicle Modeling4. Control Logics design5. Actuators Modeling6. Results
– Comparison of different control logics– Comparison of actuators– Active tractor and active trailer– Robustness
7. Conclusion
Alireza Izadi, MeccPhD, Three and a half year Evaluation 27/32
• Active tractor has the worst maneuverability, even worse than passive vehicle,• Both combinations are worsening the rollover threshold and the active roll control is
recommended to use only for fully active vehicle.
Active combinations
Comparison of ControllersActive air springs
Actuators capability
Actuators comparison
Active combinations and 5th wheel study Robustness AnalysisRESULTS:RESULTS:
Active combinations:1. Active tractor2. Active semitrailer
The comparison considers:1. Rollover threshold improvement in steady state maneuver2. Maximum speed for a severe DLC maneuver
Fully Active Active Tractor Active Semitrailer Passive
Rollover threshold Improvement (%) 7.64 ‐15.96 ‐4.59 0
Maximum speed in DLC (km/h) 112 90 102 98
Table 5. Rollover improvements in steady state maneuver and maximum speed in a severe transient maneuver for active combinations.
90
Active Tractor
112
Fully Active
Alireza Izadi, MeccPhD, Three and a half year Evaluation 28/32
Active Roll control design process
1. Introduction2. Methodological approach3. Vehicle Modeling4. Control Logics design5. Actuators Modeling6. Results
– Comparison of different control logics– Comparison of actuators– Active tractor and active trailer– Robustness
7. Conclusion
Alireza Izadi, MeccPhD, Three and a half year Evaluation 29/32
Robustness to payload positionRamp steering (steady state maneuver, 60 km/h)
Payload position for three controllers
Standard X +15% X ‐15% X ‐25% Z +15% Z ‐15% X +15% Z +15%Improvement (%) 7.6 9.4 8.7 8.8 7.5 6.0 10.4
Comparison of ControllersActive air springs
Actuators capability
Actuators comparison
Active combinations and 5th wheel study Robustness AnalysisRESULTS:RESULTS:
The robustness analysis was done for different positions of maximum payload• X is the distance of center of payload to hitch
• Z is the height of center of gravity of payload
Table 7. Robustness of active air springs to different payload positions and different controllers.
• All the three controllers are robust to payload positions and even the improvementin the worst condition is more than standard position
• The robustness of minimum order optimal controller is very good for our roll controlsystem.
• Minimum order control is confirmed for its robustness
Alireza Izadi, MeccPhD, Three and a half year Evaluation 30/32
Conclusion
Within the constraints and limitation of our system:1. The improvement is comparable with active anti-roll bars2. The energy consumption is low3. The costs are very low and easy to implement
Active air springs Active anti‐roll bars
Main features
Rollover preventability (%) 7.64 17.99
Robustness
Energy consumption of actuators [W] 1650 2118
Installation cost 0 high
Operational cost Very low high
All in all, considering the actuators, rollover threshold improvement, loadtrasnfer reduction, energy consumption and costs:Active air springs are the most proper compromise for this rollover controller.
Alireza Izadi, MeccPhD, Three and a half year Evaluation 31/32
I APPRECIATE YOUR CONSIDERATION.Alireza Izadi