Cloud-based battery management: a solution to complex degradation

The widespread adoption of electric vehicles is dependent on ease of use: rapid charging is a key factor. However, this comes with significant challenges for safety and can speed up Lithium-ion battery degradation, reducing performance and life. Cloud-based battery management and how it can optimise charging for individual vehicles without accelerating battery ageing provides a pathway to this objective.

As EV take-up increases, not everyone will have access to overnight charging at home. Those needing to charge on-the-go using public charging infrastructure will want this process to happen as quickly as possible. To maintain convenience and align with our expectations learned from internal combustion engine vehicles, a target for vehicle manufacturers is to make recharging as quick as filling with petrol. However, Lithium-ion (Li-ion) batteries are extremely sensitive and rapid charging accelerates battery degradation in some circumstances. Moreover, individual usage patterns will result in unique battery ageing that increases the complexity of providing appropriate solutions.


Causes of degradation

Three of the key factors that contribute to degradation in Li-ion batteries are temperature, state of charge (SoC) and charge current, with each of these having a different effect on how the cell ages.

When a Li-ion cell is operating at a higher than optimal temperature the rate of solid electrolyte interphase (SEI) layer formation and growth can increase leading to heightened lithium consumption. It can also cause a higher rate of cathode oxidisation that results in loss of positive electrode active material. Both phenomena degrade battery performance and life. At the other end of the scale, if the temperature is too low there is the potential of lithium plating. This is the formation of lithium metal deposits on the surface of the anode, which causes rapid degradation and can result in hazardous conditions that pose a safety concern such as thermal runaway.

State of charge is the ratio of the amount of charge stored in a battery relative to the total charge that battery can store. At high SoC, the increased instability between electrode and electrolytes can cause increased chemical reactions. This accelerates degradation of the electrolyte and both active materials. Low SoC can also cause degradation due to contraction and subsequent damage to the negative electrode and surrounding SEI layer.

High charging currents can also contribute to degradation, particularly at low temperatures. Higher charging currents cause greater average current density at the negative electrode. This lowers the negative electrode potential, which in turn increases the propensity of lithium plating. This can cause rapid degradation and creates risk of thermal runaway. It is heavily dependent on cell temperature and the current magnitude seen by the anode during charge: the higher the charge current and lower the temperature, the bigger the risk. If conditions are favourable for lithium to plate on the anode surface quickly, it can form dendrites, metallic microstructures that consume lithium, increase resistance and pose a safety risk.


Mitigating degradation

The considerable scope of influencing factors such as temperature, SoC and current result in a wide variation of Li-ion battery ageing characteristics. Sensitivity to these parameters is also highly design dependent, with individual cell designs behaving differently. But, by using vehicle data to determine the complex changes in cell performance and its principal causes, it is possible to mitigate degradation.

A baseline charging profile is developed for the vehicle with on-board analysis evaluating capacity and power fade state of health metrics. When there is deviation from the original beginning of life characteristics, the data is passed to the cloud when the vehicle is plugged in during rapid charging.

In the cloud, incremental capacity analysis (ICA) is used to investigate the capacity and health of the Li-ion batteries. This approach goes beyond standard state of health estimation. The cloud-based evaluation algorithm can distinguish the type of degradation. In this case of capacity fade, this is from three main types: loss of lithium, negative electrode active material loss, or positive electrode active material loss. The combination of the capacity and resistance change symptoms can then be used to identify the root cause of the Li-ion cell ageing.


Creating EV differentiation

With this information it is possible to recalibrate the battery management system for the unique challenges of that individual vehicle. New rapid charging current limits are set and an optimised charging strategy is created. With continuous recalibration of the battery management system on a vehicle-by-vehicle basis, maximum charging capability can be achieved while offering protection against lithium plating.

Cloud-based battery management has the potential to enable faster, safer charging without reducing battery life. Moreover, it’s agnostic, so applicable to any Li-ion cell chemistry or format. For vehicle manufacturers, this solution to battery degradation has the potential to create differentiation amongst EVs, providing a competitive advantage in terms of enhanced convenience, reduced recharging times and without compromising warranty, performance or battery life.




Coming Soon. Or Here Already? Quantum Computing-as-a-Service


Alongside Oxford’s expressed commitment to advancing AI technologies, delivering a quantum compute capability to the commercial sector in a service format is just a effervescent field of enquiry and investment for both the city and the university. The latter is reckoned to be the UK’s largest and most diverse centre for quantum research with 38 operational research teams focused on harnessing quantum effects in a new generation of devices that will outperform existing machines.

And some of this endeavour has found its way to real-world application, most notably with Oxford Quantum Circuits, who operate the UK’s only commercially-available quantum computer  in the UK. The company’s Quantum Computing-as-a-Service (QCaaS) platform has been put to work, most notably in a project managed by Cambridge Quantum to address one of the most pressing challenges of the quantum era, the threat to security encryption. Cambridge Quantum used Oxford Quantum Circuits’ QCaaS platform to validate their cybersecurity approach by using extracts verifiable quantum entropy from quantum computers to generate superior cryptographic keys.

Launched in July 2021, Oxford Quantum Circuits’ confident march into the commercial PAYG market identified a range of enterprise applications where a quantum compute capability has the potential to generate exponential gains, including supporting Oxford’s disciplinary focus on AI, with quantum offering the capability to develop yet more powerful algorithms with endless application.

But the reach of quantum will extend far beyond the application of AI. The early adopters of QAAS services are expected to be the pharmas in their search for better predictive health models and therapies, financial institutions seeking more reliable assessments of trading and risk management strategies, energy generators, especially in fields such as battery chemistry and battery management systems (BMS) and organisations concerned with cryptography and national security.

As part of the technology maturity cycle however, the enterprise application of QAAS is perhaps still some way off. Amazon Bracket, the environment designed to enable the testing and validation of quantum algorithms is currently dominated by researchers and government agencies, such as the Italian National Institute for Nuclear Physics, rather than a phalanx of commercial companies. But for sectors where the dividend is significant, the adoption rate will pivot quickly. The AI/ML experience tells us that the banking and financial sectors typically have the muscle to invest in nascent technologies, especially as the wins for first movers can be significant while less adventurous competitors languish, limited by the constraints of classical computing.

Thus expect QAAS customers in the first instance to come from the banking and finance services industry as they focus on increasing the speed of trade activities, transactions, and data processing manifolds.

Alongside the finance sector, expect to see the pharmaceuticals flock to quantum, again driven by first mover advantage. By the time this pattern is established, QAAS will be as common as classical cloud-based computing is today, in other words quickly becoming ubiquitous in most enterprise contexts and according to KPMG, worth US$86 billion by 2040.

Read more about quantum’s pioneers, including Oxford’s Ilana Wisby here

Consortium of Investigative Journalists lays bare SARs failings

The International Consortium of Investigative Journalists report into the global banking’s sector use of Suspicious Activity Reports or SARs as flags of convenience for laundering dirty money has laid bare the full extent of global capital movements from illicit origins to respectable destinations. One institution alone, Deutsche Bank, filed SARs that according to the FT totalled $1.3tn of transactions, providing a sobering perspective of the size of the problem at hand. While pretty much every major banking institution has been named in the leak and will be reviewing the efficacy of their Due Diligence and KYC, it is apparent that the sector’s emphasis will now certainly shift to more conscientious use of active investigation of capital provenance and rely less on passive SARs. The question is, how will banks make a fist of this need to more actively investigate the provenance of capital moving through their businesses and how to they claw back money that lands outside the system?

Consistent with most conventional wisdom, the starting point is aiming to prevent dark money entering the system in the first place. What is less apparent is exactly how low the due diligence bar is as a protection against fraud. The SARs scandal has now laid this bare. Most responses in the financial sector commence after the DD stage when deals have collapsed or turned sour applying ‘after-the-fact’ analysis of probity and in almost every case, the primary actor should never have been entertained, as in a recent property investment fraud where the most cursory of checks would have uncovered public records of bad character, or in relation to Wildcard’s COO, Jan Marsalek, about whom red flags had been raised years before his hand in one of the more flagrant financial deceits became fully apparent in June last year.

While prevention is always better than cure, if things do go wrong, investigation conducted through traditional legal protocols such as bankruptcy proceedings or forensic accounting rarely succeed, because these are precisely the toolsets the fraudster aims to outwit from the get-go. In the case of the investment fraud above, a law firm with the full support of the courts, had made no headway on the perpetrator’s whereabouts, any known assets or sources of income after 8 months of enquiry.

In such circumstances, different and far more effective investigative protocols are required, informed by military know-how with law enforcement and cyber insight. In this particular case, within three weeks, an independent investigations firm had applied a targeted methodology and unique intelligence collection tools to develop a full profile of the fraudster, including multiple addresses, known associates and likely sources of income. Further investigation identified a network of cash-rental properties and other laundering enterprises that gave the courts the basis for issuing warrants and seizure of property, all at a cost of 1% of the funds recovered.

If principle one is to go beyond vanilla due diligence, then principle two is to deploy investigative protocols that the fraudster will not have prepared to obviate from the outset of their criminal adventure.

Principle three is to mesh these capabilities into an investigative capability that transcends national boundaries. As the SARs scandal emphasises, it is the very movement of capital across territorial borders that enables it to evade tracing and detection, especially in what might be termed hostile jurisdictions.

In a recent investigation for a European investment bank that had lost $800m in a fraud committed by a Russian oligarch, seven years of pursuit with a legal team with recourse to several European courts had failed to make inroads into recovering the misappropriated money. In short order measured in weeks, pan-national investigators were able to identify a network of people of interest to the courts who manifestly were living beyond their income, and identify a number of key actors who held governmental positions. This development not only gave the courts a foothold to bring individuals into the legal system for redress, but also to charge a state in being complicit in the fraud. This positive outcome has transformed seven years of frustration into legal options that allow damages to be awarded and investor’s money to be recovered.

Investigation of financial crime in the globalised economy therefore must scale across jurisdictions. Criminals understand the playbook of the authorities from the application of predictable, hidebound legal processes to the limitation for many forms of enquiry to simply stop at national boundaries. In short, the investigation capabilities need more firepower than the fraudsters.