Quantum Computing in Mechanical Engineering and Design for the Mobility Industry

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September 21, 2022


Quantum Computing


Quantum Computing in Mechanical Engineering and Design for the Mobility Industry

With the proliferation of self-driving autonomous vehicles, sea-going vessels, trains, and micro-mobility, all operating across complex, connected transportation networks, the need to solve multifaceted problems at faster than real-time requires a paradigm shift in computing power and processing speeds. With the exceptions of some niche research and development projects that are discussed in more detail below, most manually driven or self-driving autonomous vehicles in addition to other forms of transportation, utilise classical computing. Here, classical computers manipulate ones and zeros to complete operations.

Limitations in classical computational power may cause bottlenecks in mobility development, design and manufacturing. For example, all mobility sectors use some form of cloud computing, machine learning and/or Artificial Intelligence (AI) to improve efficiency, safety, and journeys in general whilst improving sustainability and mitigating climate change. With mobility development, design, and manufacturing evolving into more sophisticated domains requiring specialist technologies, improvements in computational processing power and speed are required.

To combat some of the limitations of classical computing, mobility manufacturers around the world are investigating quantum computing. Quantum computing may be used in a range of applications in the mobility sector, from manufacturing and synthesis of novel materials to traffic control and self-driving vehicles. The effect of quantum computing on the mobility sector is expected to be significant. For the automotive industry alone, one-tenth of all potential quantum computing use cases under exploration could benefit the industry, with the economic impact expected to be in the region of US$2-3 billion by 2030.

Benefits and Shortfalls of Quantum Computing

Quantum computing has the advantage of being able to process commands and data much faster than classical computing, since it is based on quantum physics rather than algorithms and mathematics. Instead of ones and zeros as with classical computing, quantum computing utilises quantum bits, also known as ‘qubits’, which are orders of magnitudes faster at processing commands whilst also retaining the ability to perform multiple calculations in parallel.

Quantum computing techniques can be used to simplify and improve transportation network efficiency, while other forms will enhance energy generation and storage using complex algorithms that can only be interpreted using quantum computing systems. This technology can also aid mobility organisations in increasing or refining kinetic characteristics of materials for lightweight mobility structures and adhesives, as well as assisting in the development of efficient powertrains through improvements to aerodynamics, heat rejection, and power generation.

These computers are incredibly sensitive, requiring precise pressure, temperature, and insulation to function properly. Because measurement mistakes tend to arise when these devices interact with external particles, they are sealed and must be controlled using conventional computers. To prevent atoms from moving, colliding with one other, or interacting with the environment, quantum computers must operate in close to zero air pressure, an ambient temperature close to absolute zero (-273°C), and be insulated from the earth’s magnetic field. Furthermore, because these devices only run for extremely brief periods of time, the information can be destroyed very easily and cannot be preserved, making data recovery much more difficult. They are also currently prohibitively expensive and so are only deployed for specialised projects at present.

Innovations in Quantum Computing for Mobility Engineering

The German automotive giant, BMW, has outlined plans on how they will utilise quantum computing for vehicle development, design, and configuration optimisation. This relates to engines, transmissions, instrumentation, sensors, and even interior options. Before moving into series manufacturing, newly designed automotive components must be thoroughly tested; prototype vehicles are created for this purpose. However, this is prohibitively expensive and some type of frontloading technique involving simulation for prediction is therefore required. BMW have therefore developed a Quantum Approximate Optimisation Algorithm (QAOA) that provides the optimum configuration of components based on their intended purpose.

The German Aerospace Centre (DLR) is investigating novel materials for higher-capacity batteries and fuel cells for use in powered flight. DLR scientists are currently simulating electrochemical processes in energy storage devices using a quantum computer. This enables the materials to be designed and developed in a way that improves the performance and energy density of batteries and fuel cells, making them feasible for commercial flights. The DLR scientists are comparing quantum chemical interactions that occur for several new materials and electrode architectures. In addition, they want to utilise quantum computing to optimise the design of batteries to ensure optimum chemical bonding energy is achieved. Finally, the design of fuel cells utilising hydrogen and oxygen is being investigated using these quantum algorithms.

IBM has collaborated with many automakers to develop batteries for electric vehicles, which will be powered by quantum computing. The intricate chemistry of lithium-ion batteries, according to IBM, can be entirely understood in 2–3 years. In comparison, they claim that doing the same study using standard computing would take decades.

The Future of Quantum Computing for Mobility Engineering

Electric, autonomous, connected, and shared technologies, which are rapidly evolving, are shaping the future of mobility. Expediting transportation development, design, and optimisation is also particularly important. Organisations should therefore clearly define their strategic mobility roadmaps to coincide with design and developments in quantum computing if wanting to realise the full benefits of these systems. Whilst most aspects of quantum computing will not be economically viable for at least 10 years, mobility organisations should continue to explore possibilities in the short-term relating to mechanical design and/or optimisation. For instance, they might start by determining where quantum computing might provide most benefit within their mobility organisation and develop research collaborations and intellectual property with quantum computing specialists.

Development and design of cybersecurity (either physical hardware or software) is one potential market that would suit quantum computing. With the formation of more complex connected mobility, quantum encryption will be critical to the long-term viability of linked mobility since a single failure might have catastrophic implications.

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