On-line Damping Estimation in Road Vehicle Semi-active Suspension Systems

Savaresi, Dario; Favalli, Federico; Formentin, Simone; Savaresi, Sergio M.

doi:10.1016/j.ifacol.2019.09.108

Cited by 12 publications

(8 citation statements)

References 6 publications

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“…In so doing, all the trips are compared to the computed baseline behaviour of the single car and used to monitor the vehicle life to capture the effect that driving style and road state have on the vertical dynamics in an integral sense, i.e., over the vehicle life-cycle. This is different from the existing fault-detection approaches, see e.g., [13], [14], [15], [16] for the suspension system, which of course are tailored to detect individual anomalous events rather than tracking how usagerelated wear develops. The paper is organized as follows.…”

Section: Introductionmentioning

confidence: 90%

Vehicle Vertical Wearing Index (V² WI): active monitoring of wearing and aging of vertical-dynamics components in four-wheeled vehicles

Gelmini

Centurioni

Pivaro

et al. 2020

2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)

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Being able to assess the state-of-health of a vehicle opens of course many possible applications. All the more so if the ongoing degradation of the monitored components can be provided continuously as the vehicle life extends over time. In modern shared mobility systems, thanks to which migration from ownership to usership models should eventually take place, developing means to actively monitor the state of the vehicle fleet is crucial to improve business models and feasible and predictive maintenance plans. Within this challenging context, the present paper focuses on the monitoring of the vehicle vertical dynamics, to understand, from the analysis of measured data, which is the combined effect of drivingstyle and introduce road pavement roughness in determining the usage profile of the vertical-dynamics-related components of the vehicle, mostly the suspensions system. The proposed cost function concisely represents such wearing process, with the advantage of not requiring detailed parametric models of the vehicle dynamics and of the components themselves. The approach is tested on more than 9.000 km of trips carried out on four different vehicles, allowing to prove the effectiveness and generality of the approach.

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Section: Introductionmentioning

confidence: 90%

Vehicle Vertical Wearing Index (V² WI): active monitoring of wearing and aging of vertical-dynamics components in four-wheeled vehicles

Gelmini

Centurioni

Pivaro

et al. 2020

2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)

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“…According to the considered dynamic behavior of the semi-active damper, the estimation methodologies are classified into two categories. In the first one, the parallel Kalman filters (Koch et al, 2010) and the data analysis methods (Savaresi et al, 2019) were developed to estimate the damper force, ignoring the dynamic characteristics of the semi-active damper. The second category is developed based on the dynamic damper models (Tudon-Martinez et al, 2018;Pham et al, 2019a;2019b;2019c;Vela et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Real-time Damper Force Estimation for Automotive Suspension

Pham

Tran

Sename

et al. 2022

Period. Polytech. Transp. Eng.

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The real-time knowledge of the damper force is of paramount importance in controlling and diagnosing automotive suspension systems. This study presents a generalized H2/LPV observer for damper force estimation of a semi-active electro-rheological (ER) suspension system. First, an extended quarter-car model augmented with the nonlinear and dynamical model of the semi-active suspension system is written into the quasi-LPV formulation. Then, the damper force estimation method is developed through a generalized H2/LPV observer whose objective is to handle the impact of unknown road disturbances and sensor noise on the estimation errors of the state variables thanks to the H2 norm. The measured sprung and unsprung mass accelerations of the quarter-car system are used as inputs for the observer. The proposed approach is simulated with validated model of the 1/5-scaled real vehicle testbed of GIPSA-lab. Simulation results show the performance of the estimation method against unknown disturbances, emphasizing the effectiveness of the damper force estimation in real time.

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“…This model is validated experimentally, demonstrating that the observer developed is adequate and accurate. 12 Savaresi et al 13 present an approach for estimation of damping parameters in semi-active suspension systems, based on inertial measurements. The proposed method is, then, validated experimentally, showing its effectiveness.…”

Section: Introductionmentioning

confidence: 99%

Optimization of vehicle suspension parameters based on ride comfort and stability requirements

Silva

Reinaldo

Montenegro

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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The use of optimization methods in engineering is growing, allowing the best possible way to fulfill the requirements of the project. For vehicle suspensions, there are various conditions, which involve comfort, safety, stability, maneuverability, among others. A safety and stability evaluation is carried out by several tests, including Double Lane Change. In this maneuver, the vehicle must change lanes quickly twice, allowing it to be assessed for stability in sudden movements. For ride comfort, it is common for the design to be based on the vehicle’s natural vibration frequencies. In this context, this work aims to present a methodology for optimizing the suspension parameters of a vehicle, based on the natural frequencies of vibration and the simulation of a Double Lane Change maneuver. For that, it is employed vertical and lateral dynamics mathematical models, with hypotheses that allow the adequate adaptation to the represented phenomena. Finally, Particle Swarm Optimization (PSO) is used, which is a stochastic algorithm, based on nature. It has low computational cost, with reasonable results, allowing the parameters to be estimated and comprising the two objectives simultaneously.

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On-line Damping Estimation in Road Vehicle Semi-active Suspension Systems

Cited by 12 publications

References 6 publications

Vehicle Vertical Wearing Index (V² WI): active monitoring of wearing and aging of vertical-dynamics components in four-wheeled vehicles

Vehicle Vertical Wearing Index (V² WI): active monitoring of wearing and aging of vertical-dynamics components in four-wheeled vehicles

Real-time Damper Force Estimation for Automotive Suspension

Optimization of vehicle suspension parameters based on ride comfort and stability requirements

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On-line Damping Estimation in Road Vehicle Semi-active Suspension Systems

Cited by 12 publications

References 6 publications

Vehicle Vertical Wearing Index (V2 WI): active monitoring of wearing and aging of vertical-dynamics components in four-wheeled vehicles

Vehicle Vertical Wearing Index (V2 WI): active monitoring of wearing and aging of vertical-dynamics components in four-wheeled vehicles

Real-time Damper Force Estimation for Automotive Suspension

Optimization of vehicle suspension parameters based on ride comfort and stability requirements

Contact Info

Product

Resources

About

Vehicle Vertical Wearing Index (V² WI): active monitoring of wearing and aging of vertical-dynamics components in four-wheeled vehicles

Vehicle Vertical Wearing Index (V² WI): active monitoring of wearing and aging of vertical-dynamics components in four-wheeled vehicles