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During the last decade modern advanced Automotive is based on an electro-hydraulic system which mechatronical systems consisting of sensors, processor units, is used to reduce the roll angle of the vehicle and improve electronics, and actuators have been introduced to passenger the comfort and to change the dynamic behavior of the cars. The applications ranging from adaptive cruise control, vehicle in order to improve its handling. The system is steering assist, stability control and active suspension systems actuated by hydraulic cylinders attached between the antioffer great benefits for the handling, comfort, and safety of roll bar and the chassis as seen in Figure 1, [4]. The the vehicles. At the same time any malfunction of these rolicsare sis a seen in Fit 1, and systems could compromise the safety of the driver and the hydraulics are supplied by a motor pump unit (MPU) and passengers. controlled by an electro-hydraulic control unit (EHCU).Due to this fact the operation of the system should be The MPU supplies during the operation variable hydraulic monitored and faults occurring to the system shall be flow to the system dependent on the vehicle state. The detected and isolated as fast as possible. In order to avoid EHCU consists of a pressure control valve (PCV) additional sensors, hence increasing cost and decreasing regulating the pressure, a directional control valve (DCV) reliability, model-based approaches have been gaining more controlling the direction of hydraulic flow and a failsafe and more grounds in this field. valve (FSV) with the ability to lock the system to someIn this contribution a model-based fault detection applied on a vehicle control system is presented which rely on extenthence ensuring a failsafe state.

The temperature of a Lithium battery cell is important for its performance, efficiency, safety, and capacity and is influenced by the environmental temperature and by the charging and discharging process itself. Battery Management Systems (BMS) take into account this effect. As the temperature at the battery cell is difficult to measure, often the temperature is measured on or nearby the poles of the cell, although the accuracy of predicting the cell temperature with those quantities is limited. Therefore a thermal model of the battery is used in order to calculate and estimate the cell temperature. This paper uses a simple RC-network representation for the thermal model and shows how the thermal parameters are identified using input/output measurements only, where the load current of the battery represents the input while the temperatures at the poles represent the outputs of the measurement. With a single measurement the eight model parameters (thermal resistances, electric contact resistances, and heat capacities) can be determined using the method of least-square. Experimental results show that the simple model with the identified parameters fits very accurately to the measurements.

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