This paper deals with the simulation of the tire/suspension dynamics by using recurrent neural networks (RNNs). RNNs are derived from the multilayer feedforward neural networks, by adding feedback connections between output and input layers. The optimal network architecture derives from a parametric analysis based on the optimal tradeoff between network accuracy and size. The neural network can be trained with experimental data obtained in the laboratory from simulated road profiles (cleats). The results obtained from the neural network demonstrate good agreement with the experimental results over a wide range of operation conditions. The NN model can be effectively applied as a part of vehicle system model to accurately predict elastic bushings and tire dynamics behavior. Although the neural network model, as a black-box model, does not provide a good insight of the physical behavior of the tire/suspension system, it is a useful tool for assessing vehicle ride and noise, vibration, harshness (NVH) performance due to its good computational efficiency and accuracy.
In this paper the error analysis, construction and experimental assessment of performances of a new high precision six-axis load cell are presented. In a previous companion paper the conceptual design, modelling and embodiment design of the load cell were described. The new load cell is able to measure the three components of respectively a force and a moment acting on the load cell itself. The new six-axis load cell, patented by Politecnico di Milano, performs well in terms of linearity, sensitivity, accuracy and repeatability.
Systematic engineering of components that employ metamaterials has expanded the mechanical design field in recent years. Yet, topology optimization remains a burdensome tool to utilize within a systematic engineering paradigm. In this work, the design of a metamaterial shear beam for a nonpneumatic wheel using a systematic, two-level design approach is discussed. A top-level design process is used to determine the geometric and effective material properties of the shear beam, and linking functions are established and validated for the design of a shear layer mesoscale structure. At the metamaterial design level, innovative homogenization and topology optimization methods are employed to determine a set of locally optimal geometric designs for the shear layer. One geometry, the auxetic honeycomb, is shown to be an optimum to the minimum volume topology optimization problem for materials subjected to pure shear boundary conditions. As such, this geometry is identified as a candidate for the shear layer.
This work considers the impact of thermal behavior in battery design. The cell performance worsens when the operating temperature falls outside of the ideal range, and evenness of cell temperatures is sought to prevent cell electrical unbalance which may lead to performance fading and premature failure. The heat transfer between the cells and the coolant depends on the cell packaging and layout. A multi-objective optimization model is posed whose Pareto efficient designs minimize cell temperature deviations while maintaining evenness of temperature distribution. The special characteristics of the battery design problem (comparable objectives, anonymity and Pigou–Dalton principle of transfers) make it suitable for the application of the equitability preference, which is a refinement of the Pareto optimality that has not been used in engineering design. The proposed approach based on equitability is applied to compute the spacing of the cylindrical cells in a battery module that yields an optimal thermal behavior.
The design requirements of a low rolling loss non-pneumatic wheel are determined through a systematic optimization approach. In order to reduce the rolling resistance, linear elastic materials are considered instead of elastomers. To achieve an adequate compliance level, a metamaterial needs to be designed. The required metamaterial properties are determined as a result of an optimization where the metamaterial tensor components as well as the geometric dimensions are the design variables. This way the metamaterial can be designed such that the overall behavior of the non pneumatic wheel achieves the best performance in terms of compliance and contact patch pressure distribution. The resulting constitutive metamaterial properties of the shear layer can be used as prescribed constitutive properties to tailor the periodic mesostructure of a material by means of topology optimization.
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