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The influence of the inertia properties (mass, centre of gravity location, and inertia tensor) on the dynamic behaviour of the engine-gearbox system of a car is studied in this paper, devoting particular attention to drivability and comfort. The vibration amplitudes and the natural frequencies of the engine-gearbox system have been considered. Additionally, the loads transmitted to the car body have been taken into account. Both the experimental and the theoretical simulations confirmed that the engine-gearbox vibrations in the range 10 - 15 Hz are particularly sensitive to slight variation of the inertia properties. The effects on engine-gearbox vibrations due to half-axles, exhaust system, pipes and inner engine-gearbox fluids have been highlighted.

Apollo is the name of a solar prototype vehicle of Politecnico di Milano (Technical University of Milan) that has been conceived and employed for the Shell Eco-marathon® Europe competition (SEM). The paper introduces the concept design, the detailed design, the construction, the indoor tests, the successful employment at SEM and the end-of-life of the prototype. Apollo is a three-wheeler with a single driving and steering wheel at the rear. A wing with solar cells provides part of the electric energy required for running. The conceptual design started from the accommodation of the driver inside the vehicle. A number of iterations focusing on CFD (computation fluid dynamics) and wind-tunnel tests allowed to refine the total drag to less than 2N at 35 km/h. The tyre characteristic was measured on a drum. The camber of front wheels was set to 4 deg which provided the least rolling resistance.

This paper provides a review on state-of-art modern cooling systems employed for thermal cooling of electric motors for vehicle applications. In recent years, the pursue of a more sustainable and ecofriendly mobility has pushed the research towards the development of electric vehicle powertrain systems. Besides the evident advantages of the adoption of electric traction systems in terms of pollution and efficiency, the need of an effective cooling system for the electric machine components gained more and more importance in order to maintain high efficiency and ensure high durability. In fact, it is known that high temperatures can be harmful for the electric motor: besides the evident damages for mechanical parts, the influence on the permanent magnet properties is not negligible [1] [2]. In this fast-evolving environment, different solutions for the thermal problem have been researched and adopted, each one with its own pros and cons.

A new electric powertrain and axle for light/medium trucks is presented. The indoor testing and the simulation of the dynamic behavior are performed. The powertrain and axle has been produced by Streparava and tested at the Laboratory for the Safety of Transport of the Politecnico di Milano. The tests were aimed at defining the multi-physics perfomance of the powertrain and axle (efficiency, acceleration and braking, temperature and NVH). The whole system for indoor tests was composed by the powertrain and axle (electric motor, driveline, suspensions, wheels) and by the test rig (drums, driveline and electric motor). The (driving) axle was positioned on a couple of drums, and the drums provided the proper torques to the wheels to reproduce acceleration and braking. Additionally a cleat fixed on one drum excited the vibration of the suspensions and allowed assessing NVH performance. The simulations were based on a special co-simulation between 1D-AMESIM and VIRTUAL.LAB.

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.

The durability performance of brake hoses is a crucial issue for such components. Accelerated fatigue testing of brake hoses is necessary for understanding achievable lifetime, actually computation of durability is quite cumbersome due to the many different materials the hoses are made from. Despite SAE standards are available, accelerated testing of brake hoses subject to actual torsional and bending stresses seem important to provide relevant feedback to designers. In this paper, an innovative methodology for assessing the fatigue behavior of brake hoses of road vehicles is proposed. A dynamic testbed is specifically designed and realized, able to reproduce the actual assembly conditions of the hoses fitted into a vehicle suspension. The designed testbed allows to replicate actual loading conditions on the brake hoses by simulating the vertical dynamics and steering of the suspension system together with brake pressure.

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.