Software is transforming the electric vehicle (EV) charging market, solving problems related to infrastructure, interoperability, equipment and maintenance cost, and e-fuelling. The adoption of EVs is expected to outperform all expectations and account for over 50% of US vehicle sales by 2030. According to Julien Deconinck of DAI Magister, the key to mass adoption of EVs is now software, making it one of the fastest-growing sectors in the market, with EV charging software forecasted to grow to $25 billion by 2030. As EV adoption grows, the grid will face increased strain, and the number of charging points needs to meet the demands of many EV drivers. However, the interoperability of different EV charging systems remains a significant issue. The use of different protocols means there are different standards of device management, transaction handling, security, and smart charging functionalities. Fortunately, new protocols such as the Open Charge Point Protocol and communication standards such as ISO 15118 are now in place, but they will require continuous co-development by all stakeholders to increase compatibility between different charging stations and management systems. Software companies are offering essential solutions to these challenges. For instance, Kaluza uses an AI-driven approach to predict EV charging behaviour and reduce peak demand, while Zap-Map helps drivers optimize their trips from both a timing and cost perspective.
Electric vehicles (EVs) are becoming increasingly popular as more and more people become aware of their benefits over traditional petrol or diesel vehicles. EVs produce zero emissions, which means they are better for the environment, and they are also cheaper to run in the long term, despite the higher upfront cost. However, there are still several challenges that must be addressed in order for EVs to become the primary mode of transportation.
One of the biggest challenges is infrastructure. While the number of charging points is growing, it is still far away from being able to meet the demands of many EV drivers. EV drivers still must plan their journeys (especially longer ones) as the network of chargers is still inadequate, and ‘range anxiety’ remains a major stumbling block for many willing consumers. As the EV market grows, it will strain the grid. According to some estimates, we will need 1.1 EV chargers for every EV. This could increase peak electricity demand on local grids by 15–50%, requiring expensive upgrades to accommodate the increased demand.
The interoperability of different EV charging systems remains a major issue – currently it causes the problem of overnight charging for EV owners who lack off-street parking and journey planning. Having varying protocols meant there were different standards/levels of device management, transaction handling, security and smart charging functionalities. New protocols such as the Open Charge Point Protocol (OCPP) and communication standards such as ISO 15118 are now in place but will need continuous co-development by all stakeholders to increase compatibility between different charging stations and management systems.
Fortunately, software innovations are already providing solutions to many of these scaling challenges and will play a crucial role in EV adoption. From $1bn in 2021, EV charging software is forecast to grow to $25bn by 2030, making it one of the fastest-growing software sectors in the market today and a huge opportunity for value creation for founders and venture capital (VC).
One company that is tackling the issue of infrastructure is PredictEV, which is Volta Charging's proprietary network planning software. PredictEV uses machine learning to predict current and future EV charging needs, from infrastructure load requirements to site-level specifics. The software can forecast current and future demand with high levels of accuracy, allowing for precision network expansion. State governments in the US are now using PredictEV to identify optimal and equitable charging locations.
For grid management, London-based Kaluza has developed an advanced platform that helps utilities manage the impact of EV charging on electricity grid demand by providing an intelligent, distributed system that can monitor, control and optimise charging. Kaluza uses an AI-driven approach to predict EV charging behaviour and reduce peak demand, while also optimising energy costs by intelligently scheduling charging to coincide with low energy demand and lower electricity rates. Similarly, WeaveGrid’s data-driven platform ensures the grid can accommodate EVs safely by helping utilities in the US find EV drivers, analyse and gather insights on charging patterns, enrol them in managed charging programmes and EV-specific rates and incentivise beneficial charging habits.
For journey planning, there are a number of apps that help drivers optimise their trips both from a timing and cost perspective. For instance, in the UK, Zap-Map has almost all public charge points mapped, showing live status data. Its paid version offers What3words navigation, charging network filters, charger ratings and a display on the car screen.
On the issue of improving the return on investment of EV charging infrastructure and reducing the cost of a charging session, a number of software companies are tackling the challenges here. Most use cases revolve around real-time monitoring and predictive analytics. By using predictive analytics, companies can predict when charging stations are likely to be in high demand and adjust their pricing accordingly.