Optimal Linear Active Suspensions with Integral Constraint

Davis, B.R.; Thompson, A. G.

doi:10.1080/00423118808968911

Cited by 34 publications

(20 citation statements)

References 3 publications

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“…[48][49][50][51] In particular, Hrovat and Hubbard [48] use jerk-optimal LQ control to end up with an effective and systematic way of obtaining relatively fast load levelling with some -mostly minor -sacrifice in sprung mass acceleration performance. It should be pointed out that in practice a slow-acting load levelling is often used to centre the suspension against slow-changing loads.…”

Section: Special Consideration Of Handling Loading and Suspension Tmentioning

confidence: 99%

“…It should be pointed out that in practice a slow-acting load levelling is often used to centre the suspension against slow-changing loads. Davis and Thompson [49] use both integral and derivative controls in a ride quality-and handling capability-focused 7 DOF full-car model to regulate as well as maximise usable suspension deflection as the derivative action helps to decrease overshoot.…”

Section: Special Consideration Of Handling Loading and Suspension Tmentioning

confidence: 99%

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State of the art survey: active and semi-active suspension control

Tseng

Hrovat

2015

Vehicle System Dynamics

284

130

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This survey paper aims to provide some insight into the design of suspension control system within the context of existing literature and share observations on current hardware implementation of active and semi-active suspension systems. It reviews the performance envelop of active, semi-active, and passive suspensions with a focus on linear quadratic-based optimisation including a specific example. The paper further discusses various design aspects including other design techniques, the decoupling of load and road disturbances, the decoupling of pitch and heave modes, the use of an inerter as an additional design element, and the application of preview. Various production and near production suspension systems were examined and described according to the features they offer, including self-levelling, variable damping, variable geometry, and anti-roll damping and stiffness. The lessons learned from these analytical insights and related hardware implementations are valuable and can be applied towards future active or semi-active suspension design.

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Section: Special Consideration Of Handling Loading and Suspension Tmentioning

confidence: 99%

Section: Special Consideration Of Handling Loading and Suspension Tmentioning

confidence: 99%

State of the art survey: active and semi-active suspension control

Tseng

Hrovat

2015

Vehicle System Dynamics

284

130

View full text Add to dashboard Cite

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“…Different typical values of

K_{s}

K_{t}

C_{s}

, M , and m have been suggested in the literature [35,41,42,43,44,45,46]. Exploiting these parameters, the coefficients of the quarter-car transfer functions A , B , C , and D reported in Table 1 have been computed.…”

Section: A Study On the Vertical Acceleration Sensed In The Car Cabinmentioning

confidence: 99%

A Study on the Influence of Speed on Road Roughness Sensing: The SmartRoadSense Case

Alessandroni

Carini

Lattanzi

et al. 2017

Sensors

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SmartRoadSense is a crowdsensing project aimed at monitoring the conditions of the road surface. Using the sensors of a smartphone, SmartRoadSense monitors the vertical accelerations inside a vehicle traveling the road and extracts a roughness index conveying information about the road conditions. The roughness index and the smartphone GPS data are periodically sent to a central server where they are processed, associated with the specific road, and aggregated with data measured by other smartphones. This paper studies how the smartphone vertical accelerations and the roughness index are related to the vehicle speed. It is shown that the dependence can be locally approximated with a gamma (power) law. Extensive experimental results using data extracted from SmartRoadSense database confirm the gamma law relationship between the roughness index and the vehicle speed. The gamma law is then used for improving the SmartRoadSense data aggregation accounting for the effect of vehicle speed.

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“…acceleration on the body of the vehicle even without reducing the spring rate of the suspension. However, skyhook damping can increase quite radically the suspension deflection which occurs when the vehicle negotiates a deterministic track feature [4,5], and it becomes necessary to modify the control law in some manner, for example by filtering the absolute velocity to remove the low frequency variations associated with the deterministic input.…”

Section: Problem Foundationmentioning

confidence: 99%

Distinguishing Between Random and Deterministic Track Inputs for Active Railway Suspensions

Lei

Goodall

1998

Vehicle System Dynamics

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Abstrncl This paper presents and compares different control strategies for applying absolute or "skyhook" damping in active suspension systems for railway vehicles. It first examines a number of linear approaches for tiltering the absolute velocity signal in order to optimise the trade-off between the random and deterministic track input requirements, and then what can be achieved using non-linear Kalman-Filter methods is explored. Studies in this paper show that an improvement of nearly 20% in ride quality can be achieved with a linear con~plementary filter control and over 50% by using non-linear Kalman filter methods.

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Optimal Linear Active Suspensions with Integral Constraint

Cited by 34 publications

References 3 publications

State of the art survey: active and semi-active suspension control

State of the art survey: active and semi-active suspension control

A Study on the Influence of Speed on Road Roughness Sensing: The SmartRoadSense Case

Distinguishing Between Random and Deterministic Track Inputs for Active Railway Suspensions

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