Mobility and Vehicle Mechanics

1-11

Authors: Vase Jordanoska, Igor Gjurkov, Darko Danev

Transportation and traffic affect all the aspects of everyday life. To better understand traffic dynamics traffic models are developed. On microscopic level, car-following models are developed and improved during long period of time. They are used in traffic simulation tools or are the basis for operation in some advanced vehicle systems. Car-following models describe traffic dynamics through movement of individual vehicle-driver units. This paper compares Gipps model and Intelligent Driver Model (IDM) as car-following models based on driving strategies. These models are derived based on assumptions such as keeping safe distance from the leading vehicle, driving at a desired speed and producing accelerations within a comfortable range. The models are implemented and simulated in MATLAB environment and the results are discussed in terms of the ability to reproduce real driving behaviour in car following scenarios.

27-42

Authors: Clio Vossou, Dimitrios Koulocheris

The reconstruction of a vehicle collision consists of the processes of investigation, analysis and conclusions about the causes and the events during the traffic accident. In this perspective, a vehicle collision is considered in three distinct phases, the pre-collision, the collision and the post-collision phase. For the analysis of the collision phase two main approaches exist in the literature, the energy based and the momentum based one. The latter has been described in details by Brach et al. and can find a solution to a given set of parameters to reconstruct a collision. These parameters can be known or assumed using monitoring systems of the vehicle or physical evidence. In the present paper a computational model implementing the Planar Impact Mechanics (PIM) collision model has been set up in Matlab ® and its coupling with the least squares method has been investigated. As test cases, the RICSAC database, which consists of twelve staged collisions, has been used. Special attention has been given in the number of parameters which have been considered known (or assumed). The results indicate the importance of each parameter.

53-67

Authors: Giovanni Belingardi, Pier Giuseppe Anselma, Miroslav Demić

Hybrid electric vehicles (HEVs) are more and more of interest in the present vehicle market, because of the relevant reduction both in the fuel consumption and in the CO2 emission, in particular for the urban utilization. Different architectures are possible and have been considered for the vehicle hybridization. The most convenient architecture is depending on the application itself. This paper deals with a design methodology based on an optimization scheme to make the selection among the consistent number of alternatives. Optimization-based control strategies play a central role in the design process of HEVs. In early design phases they allow the comparison of different HEV powertrain architectures, thus supporting the selection of an appropriate topology. Furthermore, they lay the foundations for the development of real-time optimal energy management strategies to be implemented in the HEV on-board control unit. Fuel economy and design efficiency can overall be enhanced in this way. This paper aims at providing a comprehensive review of different optimization-based energy management strategies for HEVs. An analysis of strength and drawbacks of each considered strategy is carried out based on different evaluation criteria such as global optimality, computational cost and uniformity of the powertrain operation. Finally, simulation results for a HEV powertrain from the industrial state-of-art validate the conceptual and methodological comments related to the analysed controllers