Fahrbahnreibwertschätzung mit optimaler linearer Parametrierung

Stellet, Jan Erik; Suchaneck, Andre; Gießler, Martin; León, Fernando Puente; Gauterin, Frank

doi:10.1515/auto-2013-1037

Cited by 6 publications

(4 citation statements)

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“…Especially estimating the friction coefficient itself has been the subject of research for decades. For this reason there are numerous works that substantiate the research activities [10][11][12][13][14]. In one of the early patent applications [10] a method was derived for determining the adhesion and adhesion limit for vehicle tyres.…”

Section: State Of the Art-estimation Of Tyre-road Conditionsmentioning

confidence: 99%

“…Within all research projects, one major challenge is the on-line identification of the friction coefficient. To this subject the studies [11,12] make a significant contribution. In [11] the authors present a slip-based method for tyre-road friction estimation with higher robustness compared to previous studies.…”

Section: State Of the Art-estimation Of Tyre-road Conditionsmentioning

confidence: 99%

“…To this subject the studies [11,12] make a significant contribution. In [11] the authors present a slip-based method for tyre-road friction estimation with higher robustness compared to previous studies. Over and above that, the thesis [12] presents an estimator of the friction potential which is solely based on measurements of the driving dynamics of the vehicle.…”

Section: State Of the Art-estimation Of Tyre-road Conditionsmentioning

confidence: 99%

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A Concept for Using Road Wetness Information in an All-Wheel-Drive Control

Warth¹,

Sieberg

Unterreiner³

et al. 2022

Energies

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This paper presents a concept for using road wetness information in an all-wheel-drive (AWD) control that distributes drive torques in the longitudinal direction. Driving on wet roads requires special attention. Not only does the road surface friction coefficient decrease, but driving dynamics targets must be adjusted to prevent vehicle instability under wet conditions. As an exemplary application, the otherwise generic control concept is implemented on an AWD vehicle with a torque-on-demand transfer case. Therefore, the AWD topology of a drive train with a torque-on-demand transfer case is analysed in advance in terms of occurring torques and rotational speeds. In the following, the vehicle dynamics goals for driving in wet road conditions are described—divided into primary and secondary goals. Starting from a state-of-the art AWD control, an adaptive control strategy is derived by superimposing a wetness coordination unit. With the knowledge of occurring road wetness, this unit adapts newly introduced parameters in order to meet the target driving behaviour under wet conditions. Lastly, the derived AWD control is implemented into a 14-DOF, non-linear vehicle model in Matlab/Simulink, which is used as a virtual plant. The performance of the developed concept is assessed by the driving maneuver “Power On Cornering“ (PON), which means an acceleration out of steady-state circular motion. As its essential benefit, the AWD control enables a maximum spread between driving stability, agility and traction under combined dynamics when using wetness information. The newly introduced wetness coordination unit uses only a few additional and physically interpretable key parameters for this purpose, without significantly increasing the controller complexity.

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Section: State Of the Art-estimation Of Tyre-road Conditionsmentioning

confidence: 99%

Section: State Of the Art-estimation Of Tyre-road Conditionsmentioning

confidence: 99%

Section: State Of the Art-estimation Of Tyre-road Conditionsmentioning

confidence: 99%

See 1 more Smart Citation

A Concept for Using Road Wetness Information in an All-Wheel-Drive Control

Warth¹,

Sieberg

Unterreiner³

et al. 2022

Energies

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“…An adaptive BFD is a novel approach, which depends on a continuous estimation of the current adhesion coefficient. Solutions for that estimation are presented in [23, 31–33]. The principle of the adaptive BFD is illustrated for a front‐wheel drive and an estimated adhesion coefficient

μ_{est} = 0.6

in Fig.…”

Section: Approaches For An Increase Of Energy Recoverymentioning

confidence: 99%

Brake force distributions optimised with regard to energy recovery for electric vehicles with single front‐wheel drive or rear‐wheel drive

Spichartz

2019

IET Electrical Systems in Transportation

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Energy recovery by means of braking with the electric machine helps to extend the cruising range of electric vehicles. By optimising the recuperation system, the total energy efficiency is increased. In general, using a usual brake force distribution the capability for recuperation is not equal for every type of drive train. Usually, four-wheel drives are advantageous in comparison to drive trains with only one driven axle. Regarding the single drives, generally, a front-wheel drive provides a higher capability for recuperation than a rear-wheel drive. This is mainly due to the dynamic axle load shift, which occurs during decelerations. In order to increase the energy recovery of electric vehicles with single drive, an adaptive brake force distribution is presented and compared with other brake force distributions in this study. It uses the knowledge of the currently available adhesion coefficient between tyre and road. The positive effect on the recuperation without impairing the braking performance on a straight road is demonstrated based on simulations. In curves, the lateral forces additionally need to be considered to guarantee the stability of the vehicle, especially relating to electric vehicles having a rear-wheel drive. Fig. 1 Typical drive train topologies with one central electric machine (based on [1]) (a) Front-wheel drive, (b) Rear-wheel drive

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