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The high amount of the existing research on estimation of the maximum tire road friction is an indicator for two things. The first conclusion that can be drawn is that the maximum friction is a very important quantity for vehicle safety and vehicle stability. The knowledge of both demanded friction and maximum available friction are of high interest in ADAS (Advanced Driver Assistance Systems) applications as the investigated ones CWS (Collision Avoidance Systems), PBA (Predictive Brake Assistant) and airbag prefiring but also for VDC (Vehicle Dynamics Control) like yaw controls or for active suspension systems. The second conclusion that occurred was that there will not be one general method that is able to estimate both demanded and maximum friction in every possible driving state and that is suitable for every type of application. There are more reasons for this statement. One is that not only the friction itself but also the physical quantities that are necessary to calculate the demanded friction and to extrapolate the maximum friction cannot be measured directly (at least not with low-cost sensors) and have to be observed. The quality of these estimated quantities depend very much on the driving condition and all the simplifications that have to be made for certain driving manoeuvres. One example is the estimation of the longitudinal speed using the wheel speeds of an not powered axle which cannot be used during braking and not at all for cars with all wheel drive. Not only the current driving condition has to be well known, but also factors as road slope and banking to allow reliable estimation. To invent a method for everyday use is also challenging because different payloads, the use of different tyres like the periodical change between normal and winter tires and changing inflation pressure have to be considered. Another limitation is the use of low cost sensors which is crucial when aiming to implement such systems in mass produced cars and not only limit the use to feasibility research for engineers. The choice of the used observer or optimization method depends very much on the uncertainties of the measured signal itself and also on the uncertainties of the simplified models that depend on which sensors exactly are available for estimation. Finally, the requirements for those methods in regard of application can be very different. Active suspension systems require an individual coefficient of friction usually but already offer some dynamical excitation or can be updated because of the vehicle reaction whereas CWS also needs reliable estimates when driving on a highway for hours without significant change in vehicle dynamics. To design a system that works in most driving states, an adaptive method switching between different approaches using different input signals depending on the most reliable quantities that are available in the current driving state seems to be the most promising method. Other environmental low cost sensors that are already used in mass production vehicles like rain or outside temperature sensors can improve those algorithms by helping to avoid bad estimates.
|Titel||Chassis.tech plus 2011|
|Herausgeber (Verlag)||ATZ live|
|Publikationsstatus||Veröffentlicht - 2011|
|Veranstaltung||Chassis.tech plus - Internationales Münchner Fahrwerk-Symposium - München, Deutschland|
Dauer: 7 Jun 2011 → 8 Jun 2011
|Konferenz||Chassis.tech plus - Internationales Münchner Fahrwerk-Symposium|
|Zeitraum||7/06/11 → 8/06/11|
Fields of Expertise
- Mobility & Production
Treatment code (Nähere Zuordnung)
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