A diagnosis-based approach for tire–road forces and maximum friction estimation

Abstract

a b s t r a c tA new approach to estimate vehicle tire forces and road maximum adherence is presented. Contrarily to most of the previous works on this subject, it is not an asymptotic observer-based estimation, but a combination of elementary diagnosis tools and new algebraic techniques for filtering and estimating derivatives of noisy signals. In a first step, instantaneous friction and lateral forces will be computed within this framework. Then, extended braking stiffness concept is exploited to detect which braking efforts allow to distinguish a road type from another. A weighted Dugoff model is used during these 'distinguishable' intervals to estimate the maximum friction coefficient. Very promising results have been obtained in noisy simulations and real experimentations for most of the driving situations.

A technical survey on tire-road friction estimation

“…Then, they estimated the friction coefficient utilizing nonlinear method of optimization to minimize the error between estimated lateral force and lateral force provided by Dugoff model. In another study, a new algebraic filtering technique was used by Villagra et al [121] to estimate the longitudinal and lateral force and slip ratio, then they used a weighted Dugoff model to estimate the friction coefficient, for instance for the longitudinal direction simplifying the Dugoff equation gives: …”

Dual Mode Vehicle with In-Wheel Motor: Regenerative Braking Optimization

“…To adapt this estimation to the road conditions, an approach is to use the extended braking stiffness (XBS, defined as the derivative of the friction coefficient) [9,10]. It needs to be close to this limit to adapt accurately.…”

The potentional application of artificial intelligence in motor vehicles braking system performance

“…Analizirano je nekoliko radova koji se bave ovom problematikom. U [52,53,54] su korišćeni pristupi bazirani na statičkom modelu interakcije pneumatik-tlo koji uzima u obzir jedino klizanje točka kao ulazni parametar. U [53] je matematičkom modelu dodat neuronski model kako bi se eliminisao uticaj pojave nelinearnosti tokom određivanja sile kočenja pomoću klasičnih modela.…”

“…Kao što je već pokazano u literaturi [52,53,54,101] prilikom analize sila i momenata koji deluju u kontaktu pneumatika i tla tokom kočenja najprikladnije je krenuti od tzv. modela četvrtine vozila, koji podrazumeva da se tokom analize posmatra dinamičko ponašanje samo jednog točka.…”

“…Imajući u vidu da su genetski algoritmi, kao jedna od metoda veštačke inteligencije, široko korišćeni bilo samostalno za optimizaciju parametara procesa i optimizaciju strukture sistema [180,181,182,183] ili u kombinaciji sa ostalim metodama veštačke inteligencije [51,52,53,54], ovde su istraživane njihove mogućnosti u pogledu moguće primene u oblasti razvoja inteligentnih osobina kočnog sistema. Posebno je istraživana mogućnost kombinovanja genetskih algoritama sa metodom veštačkih neuronskih mreža u cilju formiranja hibridnog sistema pomoću koga bi se moglo inteligentno upravljati performansama kočnog sistema, a u cilju ostvarivanja optimalnog klizanja točka u kontaktu sa tlom.…”