The complexity is increasing rapidly in many areas of the automotive industry. The design of an automobile involves many different engineering disciplines, e. g., mechanical, electrical, and software engineering. The software of a vehicle comprises millions of lines of code. Further, the manufacturing, logistics, distribution, and sales of a vehicle are highly complex. There is an immense need for solving simulation problems, e. g., in battery chemistry, an essential enabler for technological advancements for electric vehicles. In all these domains, myriads of optimization, simulation, and machine learning problems arise. Quantum computing-based approaches promise to overcome some of the inherent scalability limitations of classical approaches. This article investigates quantum computing applications across the automotive value chain and identifies several high-value problems that will benefit from quantum-enhanced solutions.
@article{arxiv.2103.07433,
title = {Quantum Computing: Towards Industry Reference Problems},
author = {Andre Luckow and Johannes Klepsch and Josef Pichlmeier},
journal= {arXiv preprint arXiv:2103.07433},
year = {2021}
}
Comments
This is a pre-print of an article published in DIGITALE WELT Volume 5, issue 2. The final authenticated version is available online at: https://doi.org/10.1007/s42354-021-0335-7