Two-dimensional Spatial Optimization for Electric Motorcycle Powertrain Elements using Mixed-integer Programming

TL;DR

This paper develops a 2D optimization framework for electric motorcycle powertrain component placement, considering irregular geometries and orientations, using mixed-integer quadratic programming to improve design efficiency and performance.

Contribution

It introduces a novel MIQP-based model for 2D placement of irregular components with near-continuous rotation, enhancing design space utilization and handling complex geometries.

Findings

Higher geometric complexity improves placement solutions.

The framework achieves a 2.5% performance increase over existing designs.

Computation times are manageable even with increased complexity.

Abstract

This study presents a framework for optimizing the two-dimensional (2D) placement of electric motorcycle powertrain elements, accounting for the position, the orientation and geometric irregularities. Specifically, we construct a 2D placement model at the component level in which we include near-continuous rotation of components and allow for irregular subsystem geometries to make optimal use of the limited design space. Second, we introduce linearization techniques for the trigonometric constraints and formulate the placement problem as a mixed-integer quadratic program (MIQP). Finally, we demonstrate our framework on two electric motorcycle powertrain topologies and study the influence of the geometry complexity on the placement solutions. The results show that gradually increasing complexity leads to more manageable computation times and higher the complexity solution improves handling performance by 2.5% compared to the benchmark placement found in existing electric motorcycles.