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One of the way for improving environmental performances of car propulsion system is the adoption of hybrid systems where the internal combustion engine (ICE) is coupled or temporary overtaken by an electric motor. The reference prototype of this article is the FIAT Multipla Hybrid where are possible three functional modes: Pure Electric mode, Serial Hybrid and Parallel Hybrid. Particularly it was approached the torque splitting algorithm applied to the parallel hybrid one; the work was first tested in simulation, after implemented in the electronic control units and finally tested on the field using the test bench of the 10 hybrid vehicles that belongs to the Atena Project [1].

The electric storage equipment plays a relevant role in the framework of the minimum impact vehicles. Speaking about both electric and hybrid vehicles the battery still remain a necessary subsystem in order to realise an energy buffer and/or a power buffer. Normally the batteries (i.e. lead acid, Ni–MeH, semibipolar) are delivered from the manufacturers without a SOC (State of Charge) indicator. In this article it will be approached a methodology to estimate the state of charge of a battery using only the current and voltage signal. The algorithm came from a previous patent of Centro Ricerche FIAT and it will be specially modified in order to be applied to a battery system of an electric vehicle propelled by a 15 kW motor and with a 5KW fuel cell auxiliary power unit. The aim of the technology is to overtake the difficulties from the use of in-site sensors (i.e. optical or chemical).

The AICC is an assisting system for controlling relative speed and distance between two vehicles in the same lane. The AICC system may be considered as an extension of a traditional cruise control, not only keeping a fixed speed of the vehicle, but correcting it also to that of a slower one ahead. The main objective of this paper is to illustrate the design of the intelligent cruise control system involving the automatic control of throttle position and braking systems. There is much evidence nowadays that fuzzy approaches to real problems, where the linear control theory fails or can't provide an available and robust design solution, are often the best alternative to more familiar schemes.