Electrical machines consumed the amount of 9’346 TWh in 2019, corresponding to more than 40% of the total global electricity consumption. With the growing demand for automation of production lines and electrification of the transport industry, this value is likely to increase in the next years. Improving the performance of electrical machines will and already plays a key role in better managing our society’s energy consumption. In order to achieve this, in this work I develop the premises of a new Topology Optimization (TO) framework based on the method of moving morphable components (MMC). It allows to automatically design the best shapes of the motor’s components. Initially developed for structural mechanics, TO directly investigate the ideal distribution of material in space. This novel method often results in organic shapes. The goal of this project is to adapt an already existing TO framework from [9] adapted and written in Python, to design the winding of a linear motor.