Non-stationary Random Vibration Analysis of Vehicle with Fractional Damping

He, Lei; Qin, Gang; Zhang, Yunqing; Chen, Liping

doi:10.1109/icicta.2008.348

Cited by 25 publications

(11 citation statements)

References 12 publications

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“…For this illustration, the developed vehicle model was propelled with five constant vehicle speeds (20, 40, 60, 80 and 100 kmph) on five different road surfaces (A, B, C, D and E with respect to ISO 8608). The road profile was generated using equation (23) from He et al, 39 in which the terms n 0 and G q (n 0 ) define the reference spatial frequency and road roughness coefficient whose values are considered from Table 4, z R (t) represents the road surface roughness, V is the vehicle speed in kmph and w(t) indicates the white noise spectral density valued as unity…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

Investigation and performance comparison of ride comfort on the created human vehicle road integrated model adopting genetic algorithm optimized proportional integral derivative control technique

Anandan¹,

Kandavel²

2020

Proceedings of the Institution of Mechanical Engineers, Part K:

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This context exhaustively investigates the ride comfort performance index on the proposed active suspension vehicle system. Ride comfort in terms of occupants (includes driver and passenger) head acceleration, sprung mass vertical and pitching accelerations is considered. For this examination, a 14-degree-of-freedom human vehicle road integrated system model was extensively developed. Then, an active suspension system composed of a hydraulic actuator and proportional-integral-derivative controller is incorporated into the developed vehicle model to enhance the ride comfort. Besides, the designed controller needs to satisfy other vehicle performance indices like vehicle stability and ride safety. Accordingly, the controller parameters were optimally tunned with the help of genetic algorithm technique, on the basis of integral time absolute error criterion. The objective function was created on the basis of minimizing the integral time absolute error of sprung mass displacement, suspension working space and tire deflection responses. The entire response of human vehicle road integrated model, with the proposed active suspension system and passive suspension system on various random road surfaces (A, B, C, D and E with respect to ISO 8608) with five constant speeds (20, 40, 60, 80 and 100 kmph), was compared via surficial presentation. Furthermore, the comfort measures such as root mean square and vibration dose value from ISO 2631-1 were adopted to evaluate the severity between the occupants via head acceleration response. The simulation results showed that the suggested active suspension system significantly improved the ride comfort with guaranteed vehicle stability and ride safety.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Investigation and performance comparison of ride comfort on the created human vehicle road integrated model adopting genetic algorithm optimized proportional integral derivative control technique

Anandan¹,

Kandavel²

2020

Proceedings of the Institution of Mechanical Engineers, Part K:

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“…When a car moves at a constant velocity v, the road roughness can be viewed as a stationary process in the space domain. The differential equation of road roughness can be expressed as (He et al 2008;Zhang et al 2007):…”

Section: Resultsmentioning

confidence: 99%

GA-based multi-objective optimization of active nonlinear quarter car suspension system—PID and fuzzy logic control

Nagarkar¹,

Bhalerao²,

Patil³

et al. 2018

Int J Mech Mater Eng

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Background: The primary function of a suspension system is to isolate the vehicle body from road irregularities thus providing the ride comfort and to support the vehicle and provide stability. The suspension system has to perform conflicting requirements; hence, a passive suspension system is replaced by the active suspension system which can supply force to the system. Active suspension supplies energy to respond dynamically and achieve relative motion between body and wheel and thus improves the performance of suspension system. Methods: This study presents modelling and control optimization of a nonlinear quarter car suspension system. A mathematical model of nonlinear quarter car is developed and simulated for control and optimization in Matlab/ Simulink® environment. Class C road is selected as input road condition with the vehicle traveling at 80 kmph. Active control of the suspension system is achieved using FLC and PID control actions. Instead of guessing and or trial and error method, genetic algorithm (GA)-based optimization algorithm is implemented to tune PID parameters and FLC membership functions' range and scaling factors. The optimization function is modeled as a multi-objective problem comprising of frequency weighted RMS seat acceleration, Vibration dose value (VDV), RMS suspension space, and RMS tyre deflection. ISO 2631-1 standard is adopted to assess the ride and health criterion. Results: The nonlinear quarter model along with the controller is modeled and simulated and optimized in a Matlab/Simulink environment. It is observed that GA-optimized FLC gives better control as compared to PID and passive suspension system. Further simulations are validated on suspension system with seat and human model. Parameters under observation are frequency-weighted RMS head acceleration, VDV at the head, crest factor, and amplitude ratios at the head and upper torso (AR_h and AR_ut). Simulation results are presented in time and frequency domain. Conclusion: Simulation results show that GA-based FLC and PID controller gives better ride comfort and health criterion by reducing RMS head acceleration, VDV at the head, CF, and AR_h and AR_ut over passive suspension system.

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“…To describe the stationary characteristics of road roughness, power spectral density (PSD) is one of the applicable tools. Assuming a truck moving at a constant velocity , the road surface roughness can be considered as a stationary process in the space domain and this approach is examined in many studies [72]- [74]. The road roughness can be defined using a white noise signal with a certain power spectral density.…”

Section: B Random Road Inputmentioning

confidence: 99%

“…where ( ) represents the road roughness, the reference spatial frequency, (Ω ) is the PSD of the road disturbance input and finally ( ) is the waviness, which indicates the road's wavelengths. The waviness range is between 1.75 ≤ ≤2.25 and is taken usually = 2 [72]. By applying the same control coefficients used in the previous section as in (39)(40)(41)(42), system response is analyzed for random road input.…”

Section: B Random Road Inputmentioning

confidence: 99%

Vibration Control of Truck Cabins With the Adaptive Vectorial Backstepping Design of Electromagnetic Active Suspension System

Başaran

2020

IEEE Access

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The active suspension system is an important equipment that isolates the vibrations that may come from outside in a land vehicle. In heavy vehicles, the active suspension system can be used to dampen vibrations in the driver's cabin. The electromagnetic actuator is used as an active element in suspension system. Traditionally, the use of active suspension systems is mainly on automobiles and the studies related to heavy vehicles like trucks lack enough interest. In this study, dynamic modeling of a three-axle heavy vehicle cabin is performed with a half-car approach and it is aimed to suppress the disruptive effects coming from the road with active electromagnetic actuators. Lyapunov based backstepping control design is expressed in vectorial form for the heavy vehicle system, which is a multi-input multi-output system. To demonstrate the performance of the designed controller, a comparison has been made for the active and passive states for the truck cabin suspension system. The main feature of the applied control method is that it does not require knowing the actuator parameters, the adaptive term can handle the estimate of the actuator parameter. The stability of the proposed system has been proven via Lyapunov based arguments and given simulation works. The results obtained are important to suppress vibration, consequently, decreases the vibration exposure for truck drivers in terms of occupational health and safety aspects. INDEX TERMS Adaptive backstepping control, Truck cabin suspension system, Truck modeling.

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Non-stationary Random Vibration Analysis of Vehicle with Fractional Damping

Cited by 25 publications

References 12 publications

Investigation and performance comparison of ride comfort on the created human vehicle road integrated model adopting genetic algorithm optimized proportional integral derivative control technique

Investigation and performance comparison of ride comfort on the created human vehicle road integrated model adopting genetic algorithm optimized proportional integral derivative control technique

GA-based multi-objective optimization of active nonlinear quarter car suspension system—PID and fuzzy logic control

Vibration Control of Truck Cabins With the Adaptive Vectorial Backstepping Design of Electromagnetic Active Suspension System

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