Quantum Technology in Automotive and Manufacturing
Vehicle makers have worked with quantum computers for years. Volkswagen routed buses in Lisbon on a D-Wave system in 2019, and BMW, Airbus and Quantinuum modelled fuel-cell catalysts on quantum hardware in 2023. Since 2025, Ford Otosan has used a D-Wave application in production to sequence vehicles; the companies report scheduling time for 1,000 vehicles falling from 30 minutes to under five.
Batteries are the strongest computing case. Published estimates put the first simulations of the cathode spectra that explain battery degradation at 100 to 414 logical qubits, and we expect them around 2029–2032. We expect scheduling and logistics to stay with classical solvers and AI through at least 2035, and quantum sensing for navigation and battery monitoring is the nearest to deployment. In this course, we cover what each technology can do for automotive and manufacturing, how to judge the claims, and what to prepare now.
Course Outline
Module 1. Judging Quantum Claims (45 minutes)
Quantum computing, sensing and networking mature at different speeds, and each needs its own tests. We separate results demonstrated on hardware from company announcements and from resource estimates. We also separate the physical qubits in current machines from the logical, error-corrected qubits required for useful computation. You learn to ask which classical method a result was compared with, and which roadmap dates are commitments and which are targets. We test each question on a recent manufacturing result, a scheduling gain measured against the plant’s previous process rather than the best classical solver.
Module 2. Quantum Computing for Batteries, Materials and Production (75 minutes)
We work through the battery and materials problems with published resource estimates: cathode degradation spectra, electrolyte molecules and fuel-cell catalysts. We explain why the date for battery simulations depends on how many gate operations a machine can run. One estimate finds that a 414-logical-qubit calculation needs 20 times the gate budget IBM targets for 2033. We then cover production scheduling, paint-shop sequencing and fleet routing, where annealing has run on hardware without a demonstrated advantage over strong classical methods. We also cover engineering simulation, and quantum machine learning for perception.
Module 3. Quantum Sensing and Secure Connectivity (45 minutes)
We cover quantum navigation without satellite signals, from Q-CTRL’s airborne and ground-vehicle trials to Boeing’s four-hour flight with a quantum inertial sensor. We cover diamond magnetometers for battery current monitoring. We also cover optically pumped magnetometers for inspecting battery cells and electronics in manufacturing quality assurance. We explain why quantum radar does not suit vehicles. We also explain why connected vehicles and over-the-air updates need post-quantum cryptography rather than quantum key distribution.
Module 4. What Vehicle Makers and Manufacturers Are Doing (30 minutes)
We review named programs and what each result shows. They include Ford Otosan with D-Wave, Volkswagen’s routing pilot and battery estimates with Xanadu, Mercedes-Benz with IBM and PsiQuantum, and BMW with Quantinuum. We also cover the Airbus and BMW Quantum Computing Challenge, Hyundai with IonQ, Toyota with Xanadu and Bosch’s quantum sensing venture. For each, you learn whether it reports a production use, a hardware result, an announcement or an estimate.
Module 5. Preparing Now (45 minutes)
We show you how to sort your problems by evidence. You put battery, catalyst and materials questions on a quantum watch list, and keep scheduling, routing and supply-chain optimization on classical and AI roadmaps. You learn to track resource estimates for your own chemistries, and to benchmark every optimization pilot against the best classical solver on your own data. We cover partnerships, sensor pilots on your own platforms, and post-quantum migration for vehicles that will stay in service after 2035. In a working exercise, you draft a one-page quantum brief for your leadership.
Prerequisites
None.
Who this course is for
Executives, R&D and innovation leads, manufacturing and supply-chain program managers, and battery, materials, engineering and data teams at vehicle makers, suppliers and manufacturers. Also useful for aerospace manufacturers, and for investors who assess mobility technology.
What you’ll be able to do afterward
- Explain what quantum computing, sensing and networking can and cannot do for automotive and manufacturing today
- Read a battery resource estimate and judge when it becomes feasible
- Test a scheduling or routing claim against the best classical solver
- Assess quantum navigation and battery sensors by their field data
- Identify the battery, materials and catalyst problems worth tracking
- Plan partnerships, pilots and post-quantum migration for vehicles and plants
What you leave with
When you finish, we email you the course handbook, a PDF of every slide with notes that explain it in full. It includes a table of the use cases covered, each labelled as demonstrated, announced or estimated, with its sources. We also include a PDF copy of Quantum Systems Integration. The handbook is yours to keep.
Enrollment includes 180 days of access to the online on-demand course. Where that course is not yet published, the 180 days start on the day it is.
Where this course fits
You can take this course on its own. No technical background is assumed. For the security side, take Quantum-Safe Automotive, and for plant systems, Quantum-Safe OT and Critical Infrastructure. Quantum Technology for Chemicals and Materials covers battery and catalyst simulation in more depth. For the sensors, take Quantum Sensing Fundamentals.
Why we teach this
The material is based on Quantum Systems Integration, the reference text on quantum computing, networking, and sensing written by the course author. It also draws on faculty who work with quantum engineering and integration teams, and on the published resource estimates for each use case. We label every result in the course as demonstrated on hardware, announced by a company or estimated, so you can see how far each one has progressed.
Certificate of Completion
Upon completion, you receive a Quantum Academy certificate of completion. It confirms that you completed the course and is separate from Quantum Academy’s professional certifications.
About this program
Quantum Academy credentials are private professional credentials issued by Quantum Academy, a trade name of Post-Quantum Institute. They are not government-issued licenses, accredited degrees, or academic credit, and earning one does not guarantee employment, promotion, regulatory approval, or any other specific outcome.
Quantum Academy programs are educational and informational only, and are not legal, compliance, or engineering advice.
