Modelled optimisation approaches for laser cutting sheets simultaneously applied to EV component production

Abstract

This paper proposes that laser cutting has potential as a viable alternative to stamping for mass manufacture of thin steel components such as stator and rotor components in the electric automotive sector. Current laser cutting processes are much less efficient than stamping. However, laser cutting is much more flexible and is used for small batches and one-off production. This paper assesses the potential of performing laser cutting operations of multiple sheets or layers simultaneously. This method is referred to herein as polystromata cutting. A numerical model is used to assess the manufacturing performance of stamping, traditional laser cutting and polystromata laser cutting. Polystromata laser cutting is shown to be capable of producing parts at 37% less cost than stamping. However, polystromata remains slower than stamping, taking 79% more time to produce each stator stack. Through this research it has been identified that optimisation of polystromata processes is more complex and performance efficiency varies wildly dependent on manufacturing set-up. This work aims to provide a best practice optimisation methodology for polystromata laser cutting by assessing results using different manufacturing objectives.

Multi-layer laser cutting of electrical steel sheets applied to electric machine laminations

“…Stamping is an established process for producing shaped laminations. Bayraktar & Turgut [6] and Jayarama [7] both investigate the effect of stamping on the quality of the cut edge. M400-50A (Bayraktar & Turgut) and HYPERCO 50 (Jayarama) are the materials tested.…”

“…Salvador [12] has similarly compared the performance of laser cut and guillotined (a cutting method mechanically very similar to stamping) samples, again concluding that laser cutting introduces greater losses than stamping-like processes. Bayraktar & Turgut [6] compare four different cutting methods. On visual inspection of those results the stamped samples appear slightly better than the laser cut samples.…”

Electric Vehicle Power System in Intelligent Manufacturing Based on Soft Computing Optimization

“…Expert experience and data mining, which have high efficiency and feasibility but lack systematicity and dependability, are the two main foundations for experience-based approaches (Chopra et al 2023). The power system can be swiftly optimized and the control strategy can be designed with high efficiency and reliability using the simulation-based approach, but correctness of the simulation model and the dependability of the simulation results must be ensured (Dodd et al 2022). Genetic algorithm (GA) has powerful search and optimization capabilities as a worldwide search and optimization method.…”