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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 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.

This paper presents a validation method for indoor testing of a passenger car suspension. A study was done to design a supporting modular structure with comparable inertances with respect to a vehicle's actual suspension and body connection points. For the indoor test, the rear axle is positioned on a rotating drum. The suspension system is excited as the wheel passes over cleats fixed on the drum and transient wheel motions are recorded. The indoor test rig outputs (i.e., wheel and chassis accelerations) were compared with experimental data measured on an actual vehicle running at different speeds on the same set of cleats along a flat road. The comparison results validate the indoor testing method. The forces and moments acting at each suspension and chassis connection point were measured with a set of patented six-axis load cells. The forces, moments, wheel and subframe accelerations were measured up to 120 Hz.

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.

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.

A robust optimization approach has been applied to the design of a piezoelectric brake. The force generated by the piezoelectric actuator is transmitted to the pad shoe through a lever. The optimal design of the lever is crucial for obtaining the desired performance of the brake. Increasing the stiffness and reducing the mass of the lever is the key problem for such kind of mechatronic brake. A trade off between mass and stiffness of the lever must be obtained. Multi-objective programming (MOP) has been applied in order to achieve the best compromise. In addition to MOP, the optimal robust design method has been applied to perform the optimal design not only by considering the performance of the system (the stiffness and mass of the lever) but also by taking into account the robustness (the sensitivity to the uncertain system parameters).

Roundabouts are intersections at which automated cars seem currently not performing sufficiently well. Actually, sometimes, they get stuck and the traffic flow is seriously reduced. To overcome this problem a V2N-N2V (vehicle-to-network-network-to-vehicle) communication scheme is proposed. Cars communicate via 5G with an edge computer. A cooperative machine-learning algorithm orchestrates the traffic. Automated cars are instructed to accelerate or decelerate with the triple aim of improving the traffic flow into the roundabout, keeping safety constraints, and providing comfort for passengers on board of automated vehicles. In the roundabout, both automated cars and human-driven cars run. The roundabout scenario has been simulated by SUMO. Additionally, the scenario has been reconstructed into a dynamic driving simulator, with a real human driver in a virtual reality environment. The aim was to check the human perception of traffic flow, driving safety and driving comfort.