Wolfgang Hirschberg

On-Board Payload Identification for Commercial Vehicles

Roll over accidents of vehicles belong to the most dangerous vehicle accident scenarios on our roads. In particular, heavy commercial vehicles allow enormous changes of loads and often the drivers are confronted with unknown load conditions, e.g. container freight. This causes a persistent overturning hazard. Due to the varying load situations, the drivers of commercial trucks are therefore requested to permanently adapt their driving style in relation to the actual driving and roll dynamics of their vehicles, in order to provide sufficient driving safety. This paper therefore deals with methods to identify the payload parameters of air-sprung vehicles on different levels. Special attention is spent to examine the described onboard-identification methods for application to truck-semitrailer combinations. The online-identified relevant payload parameters are the load mass, the position of its centre of gravity and especially the height of its centre of gravity above ground. The aim of this paper is on the one hand to develop an identification approach to be able to provide more driver information about the actual overturning limit of the vehicle and on the other hand to deliver additional information about the current loading conditions of the vehicle as an input to any advanced driver assistance system or to enhanced vehicle-dynamics controllers, which take the payload height into consideration

Experimental validation of the Maxwell model for description of transient tyre forces

Modelling and simulation of safety relevant Driver Assistance Systems (DAS) and Vehicle Dynamics Controllers (VDC) which act in standard and limit situations lead to increasing accuracy demands in the description of dynamic reactions of tyre contact forces, e.g. [4], [7]. For that purpose, first-order approaches are widely applied in this field of vehicle dynamics and handling, which originate from Schlippe & Dietrich [13], were modified by Pacejka [10] and later on refined by Rill [11], [12].

Tyre Dynamics: Model Validation and Parameter Identification

The present paper deals with the experimental validation of tyre dynamics approaches as it is widely applied in tyre models for vehicle dynamics and handling. Firstly it gives a brief derivation of two modelling principles regarding the deflection velocity in the considered direction of the tyre’s deformation. This is than followed by a brief description of the performed measurement procedure. From the measurements, a set of model parameters of the considered tyre, depending on different manoeuvre speeds and frequencies, is identified, where no particular fitting parameters for the tyre dynamics are needed. Based on these model parameters, the related dynamic simulations are carried out. The comparisons show that the applied first-order model describes the behaviour quite well within a certain operation range, whereas the second-order approach cannot deliver better results in spite of the longer computational time. However, for investigations within an enlarged frequency range of the steer input and at high slip angles, a more detailed model is recommended.

Experimental validation of different approaches for thermodynamic simulation of passenger car tyres

Due to the intensified integration of simulation and modelling into the development of automotive vehicles and their assistance systems, the expectations of accuracy and computational efficiency in simulation are increasing rapidly. In addition, simulation finds more and more application in the process of vehicle homologation, which were a pure experimental discipline in the past. In any case, not only demands affecting vehicle modelling but also refined tyre modelling become more important. In recent years, with continuing refinement in tyre simulation, the needs for coping with tyre temperatures and the resulting influences on the tyre characteristics have been considered important.

Parametrisation of a Maxwell model for transient tyre forces by means of an extended firefly algorithm

Developing functions for advanced driver assistance systems requires very accurate tyre models, especially for the simulation of transient conditions. In the past, parametrisation of a given tyre model based on measurement data showed shortcomings, and the globally optimal solution obtained did not appear to be plausible. In this article, an optimisation strategy is presented, which is able to find plausible and physically feasible solutions by detecting many local outcomes. The firefly algorithm mimics the natural behaviour of fireflies, which use a kind of flashing light to communicate with other members. An algorithm simulating the intensity of the light of a single firefly, diminishing with increasing distances, is implicitly able to detect local solutions on its way to the best solution in the search space. This implicit clustering feature is stressed by an additional explicit clustering step, where local solutions are stored and terminally processed to obtain a large number of possible solutions. The enhanced firefly algorithm will be first applied to the well-known Rastrigin functions and then to the tyre parametrisation problem. It is shown that the firefly algorithm is qualified to find a high number of optimisation solutions, which is required for plausible parametrisation for the given tyre model.