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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.

The ride comfort of three Alfa Romeo cars, namely Giulietta (1955), Alfetta (1972) and 159 (2005) has been assessed both objectively and subjectively. The three cars belong to the same market segment. The aim is to let young engineers or graduate students understand how technology has evolved and eventually learn a lesson from the assessed trend. A number of cleats have been fixed at the ground and the three cars have traversed such uneven surface. The objective assessment of the ride comfort has been performed by means of accelerometers fixed at the seat rails, additionally a special dummy developed at Politecnico di Milano has been employed. The subjective assessment has been performed by a panel of passengers. The match between objective and subjective ratings is very good. Simple mathematical models have been employed to establish a (successful) comparison between experimental and computational results. The ride comfort differs substantially among the cars.

In this paper, an improved analytical model accounting for thermal effects in the electromagnetic field solution as well as efficiency map calculation of an outer rotor surface permanent magnet (SPM) machine is described. The study refers in particular to an in-wheel motor designed for automotive electric powertrain. This high torque and low speed application pushes the electric machine close to its thermal boundary, which necessitates estimates of winding and magnet temperatures to update the winding resistance and magnet remanence in the efficiency calculation. An electromagnetic model based on conformal mapping is used to compute the field solution in the air gap. The slotted air-gap geometry is mapped to a simpler slotless shape, where the field solution can be obtained by solving Laplace's equation for scalar potential. The canonical slottless domain solution is mapped back to the original domain and verified with finite element model (FEM) results.

The paper deals with the bifurcation analysis of a simple mathematical model describing an automobile running on an even surface. Bifurcation analysis is adopted as the proper procedure for an in-depth understanding of the stability of steady-state motion of cars (either cornering or running straight ahead). The aim of the paper is providing the fundamental information for inspiring further studies on vehicle dynamics with or without a human driver. The considered mechanical model of the car has two degrees of freedom, nonlinear tire characteristics are included. A simple driver model is introduced. Experimental validations of the model are produced. As a first step, bifurcation analysis is performed without driver (fixed control). Ten different combinations of front and rear tire characteristics (featuring understeer or oversteer automobiles) are considered. Steering angle and speed are varied. Many different dynamical behaviors of the model are found.

The friction estimation at the tire-ground contact is crucial for the active safety of vehicles. Friction estimation is a key problem of vehicle dynamics and the ultimate solution is still unknown. However the proposed approach, based on a simple idea and on a simple hardware, provides an actual solution. The idea is to compare the tire characteristic at a given friction (nominal characteristic) with the actual characteristic that the tire has while running. The comparison among these two characteristics (the nominal one and the actual one) gives the desired friction coefficient. The friction coefficient is expressed in vector form and a number of running parameters are identified. The mentioned comparison is an efficient but complex algorithm based on a mathematical formulation of the tire characteristic. The actual tire characteristic is somehow measured in real time by a relatively simple smart wheel which is able to detect the three forces and the three moments acting at the hub.

A wheel able to measure the generalized forces at the hub of a race motorcycle has been developed and used. The wheel has a very limited mass. It is made from magnesium with a special structure to sense the forces and provide the required level of stiffness. The wheel has been tested both indoor for preliminary approval and on the track. The three forces and the three moments acting at the hub can be measured with a resolution of 1N and 0.3Nm respectively. A specifically programmed DSP (Digital Signal Processor) embedded in the sensor allows real-time acquisition and processing of the six signals of forces/torques components. The signals are sent via Bluetooth to an onboard receiver connected to the vehicle CAN (Controller Area Network) bus. Each signal is sampled at 200Hz. The wheel can be used to derive the actual tyre characteristics or to record the loads acting at the hub.

The lightweight seat of a high performance car is designed taking into account a rear impact, i.e. the crash due to an impulse applied from the rear. The basic parameters of the seat structure are derived resorting to simulations of a crash with a test dummy positioned on the seat. The simulations provide the forces acting at the seat structure, in particular the forces applied at the joint between the seat cushion and the seat backrest are taken into account. Such a joint is simulated as a plastic hinge and dissipates some of the crash energy. The simulations are validated by means of indoor tests with satisfactory results. A tool has been developed for the preliminary design of lightweight seats for high performance cars.

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.