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Technical Paper

Industry 4.0 and Automotive 4.0: Challenges and Opportunities for Designing New Vehicle Components for Automated and/or Electric Vehicles

2019-04-02
2019-01-0504
The paper deals with the “wise sensorization” of vehicle components. In the upcoming full digitalization of mobility, vehicle components are getting more and more sensorized. The problem is why, what, when and where vehicle components can be sensorized. The paper attempts a preliminary problem statement for the sensorization of vehicle components. A theoretical basic investigation is introduced, setting the main concepts on which extended sensorization is advisable or not. The paradigms of Industry 4.0 and Automotive 4.0 are addressed, namely sensors are proposed to be used both for monitoring the manufacturing process and for monitoring the service life of the component. In general, sensors are proposed to be used for multiple purposes. Two examples of sensorized components are briefly presented. One refers to a sensorized electric motor, the other one refers to a sensorized wheel.
Journal Article

Electric Motor for Brakes – Optimal Design

2020-04-14
2020-01-0919
A multi-objective optimal design of a brushless DC electric motor for a brake system application is presented. Fifteen design variables are considered for the definition of the stator and rotor geometry, pole pieces and permanent magnets included. Target performance indices (peak torque, efficiency, rotor mass and inertia) are defined together with design constraints that refer to components stress levels and temperature thresholds, not to be surpassed after heavy duty cycles. The mathematical models used for optimization refer to electromagnetic field and related currents computation, to thermo-fluid dynamic simulation, to local stress and vibration assessment. An Artificial Neural Network model, trained with an iterative procedure, is employed for global approximation purposes. This allows to reduce the number of simulation runs needed to find the optimal configurations. Some of the Pareto-optimal solutions resulting from the optimal design process are analysed.
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