Can quantum technology improve the performance of batteries? The answer is yes. A project led by researchers at the University of Sussex is using a quantum-based sensor to measure battery behavior, with the expectation that the resulting data can be used to improve battery technology.

The project has been awarded with the University of Birmingham’s Partnership Resource Funding, UK Quantum Technology Hub Sensors and Timing. The project team also includes the Universities of Strathclyde and Edinburgh as part of the consortium.

The project addresses a crucial need to increase energy density, durability and safety in batteries, thus driving the industrial revolution towards an increasingly green ecosystem. To achieve these and other green goals, intensive research and development in these areas are needed while implementing environmental policies.

In an interview with EE Times, Peter Kruger, research professor of experimental physics at the University of Sussex, highlighted how batteries seem to be the first big market for quantum battery sensors, as EVs require large battery packs with high storage capacity. “That would mean the first significant commercial impact of quantum sensors,” said Kruger.

Battery and quantum technology

New electric vehicle control systems, including regenerative braking systems, start & stop functionality, and the electric motors that drive the wheels, all require accurate measurement and control of electrical inputs to optimize performance and avoid catastrophic failure.

An essential part of these systems is the battery current measurement sensor, which measures the battery charge and discharge level and its state of health. There are several existing technologies to create a good current sensor for vehicle battery monitoring.

At the same time, simulating the chemical structure of batteries using quantum computing makes it possible to apply these algorithms to reproduce the chemical composition inside a battery according to various criteria, such as weight reduction, maximum density, and cell assembly. This speeds up the industrialization of the battery pack itself.

The University of Sussex project

The goal of the project is to implement quantum magnetometer technology to examine if microscopic battery current flows accurately. In this way, rapid assessments of the chemistries of new and existing batteries will accelerate the creation of superior battery technology, thereby facilitating electrification.

A magnetometer is an instrument with a single sensor that measures magnetic flux density. Quantum magnetometers are based on the spin of subatomic particles. The coupling of each particle magnetic moment with the applied field is quantized or limited to a discrete set of values as determined by the laws of quantum mechanics.

Kruger pointed out that there have been many cases of lithium battery failures in recent years that have made the headlines, such as the case of Samsung’s Galaxy Note 7 smartphone. Monitoring the current flow could allow preventive actions to be taken before these battery failures occur. Quantum sensors could provide batteries with a some sort of intelligence by monitoring their health and reducing the most worn cells load.

“Current battery monitoring solutions mainly focus on measuring the voltage across batteries. This gives a good indication of the charge left inside a battery, and by measuring these voltages during many subsequent charge/discharge cycles, the charge capacity can be monitored as the battery degrades,” said Kruger.

He added, “While these measurements are useful to monitor the battery state of health, they do not tell us much about what is going on inside the battery. The quantum systems in development allow the magnetic fields generated by the battery to be measured, which are used to deduce the electrical currents that flow through the battery. This system acts as a “magnetic camera”, able to peer inside the battery.”

The research group’s aim is to develop small, low-power, portable devices that require no infrastructure and minimal running costs, thus being suitable for economic production.

The academics will also work closely with CDO2, Magnetic Shields Ltd and QinetiQ to achieve their goal. Magnetic Shields Ltd will provide the magnetic noise-free environment required to allow the sensor technology to be tested with unprecedented sensitivity.

“Large application is in the research sector, where battery manufacturers can bench-test different chemistries and cell geometries. The sensors could send diagnostic information to the on-board computer of an EV and could reduce the service interval as manual check-ups are no longer required. Battery farms are being developed as a form of renewable energy storage, and the technology can be adapted to be used as a smart-charging system, as well as monitoring the battery state of health,” said Kruger.

The big challenge at the moment is focused on raising the capacity of the batteries. “Technology-wise the sensors are not just sensitive to magnetic fields from the battery, but from all ferromagnetic substances. Much of the work we carry out is in the design of the sensors, and looking at how we can shield them from external magnetic sources. We have to think about how the system will be able to filter out the magnetic fields generated by the car’s electric motor, or quick changes in magnetic fields as around a tonne of metal passes the sensor each time a car passes in the other direction. A full supply chain for all relevant components needs to be established. We’re well underway doing that through concurrent Industrial Strategy funding,” said Kruger.

Batteries are the key to decarbonization, but improvements are needed in both chemistry and boundary technology. Lithium-ion batteries are still the gold standard technology in this field, and have come a long way. Checking each battery is an operation that has to take into account many factors, such as leaks and imperfections, which adversely affect the performance of the entire system, whether it is an electric vehicle or a simple consumer device.

By: DocMemory
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