Acoustics Simulation of Electric Drive Systems

A key design target in most modern transmission and electric powertrain systems is to minimise noise. MASTA’s NVH analysis capabilities enable the calculation of dynamic response to gear and motor excitations in terms of housing vibrations at accelerometer locations and sound power. A fully integrated full acoustic simulation is in development for MASTA Acoustic analysis is performed using the surface velocity of the housing obtained from the frequency response analysis as input to calculate the sound pressure and sound intensity. You can also specify microphone positions in the model to obtain sound pressure results at specific positions.

虚拟仿真

EV-Drive

Micro Geometry Machine Learning Optimisation

Optimising designs using high fidelity CAE analyses with a high dimensional set of inputs is difficult. Traditional global optimisation methods suffer from long run times. Local optimisation methods only find a single local optima in a space with multiple local optima. Machine learning based optimisation helps tackle both these problems. Machine Learning Optimisation builds a surrogate model from previous analyses to predict future analysis results. This model reveals regions of the optimisation space likely to yield improved results. This methodology is both efficient and can find results close to global optima. A fast micro geometry optimiser not only enables fast micro geometry design but also opens up possibilities for improved macro geometry optimisation.

机器学习、虚拟仿真

EV-Drive

NVH-Transfer Path Analysis

When running a harmonic analysis on a gearbox, an excitation, usually in the form of transmission error excites the system at the gear mesh and this translates through the model where the vibrations of the housing produce a resulting sound power. Using transfer path analysis, it is now possible to analyse the various paths that the vibrations take through the model to isolate potential areas that can be optimised to minimise the response.

虚拟仿真

Electric drive