"Within a year, I hope, we shall begin the manufacture of an electric automobile.” This was Henry Ford in 1914, writing to his good friend, Thomas Edison. While the “Edison-Ford” electric car never saw the light of day, for a variety of reasons, a century later we stand at the brink of an electric vehicle (EV) revolution.
Recent data from Singapore’s Land Transport Authority (LTA) shows that EVs accounted for 18% of the total car sales in 2023, and the EV revolution is just getting started. Singapore aims to reduce peak land transport emissions by 80% by 2050. The electrification of vehicles alongside improvements to the infrastructure to encourage walking, cycling and public transport are key initiatives that the LTA says will help the country achieve this target.
Such a mammoth undertaking is not without its challenges. However, many of them can be overcome by leveraging data.
The electric vehicle is sometimes referred to as “the smartphone on wheels”, and EVs are far more software-dependent than internal combustion engine vehicles. Whether for components such as thermal management systems, battery development or for user experience features, software is at the forefront.
The automotive industry is in the midst of a major transformation. The current changes are more dramatic and happening faster than ever before, and these changes are being driven more by software than mechanical engineering. This is putting pressure on legacy automakers who are struggling to shift to new ways of managing data and software development — artificial intelligence (AI), containers, open source data services, and more — while simultaneously maintaining significant legacy IT systems.
The key to automotive transformation is software and the data it both produces and processes. Winning in this market will require flexible and highly responsive software-driven development processes that make use of fleet data as well as delivering consumer-focused services. Firms will need to attract top-level coding talent, and they will also need a modern IT infrastructure for software development, testing, simulation such as digital twins, analytics, and more.
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For Singapore — which is not a traditional automotive-producing country — the key to achieving its 2030 Zero-Emission Vehicle Deployment Goal lies not in just transforming logistical infrastructure but also putting in place a comprehensive data management platform that is able to analyse volumes of data measuring anything from traffic patterns, locations of charging stations, battery management, and energy consumption in the grid.
Why data is at the heart of the EV ecosystem
A synergy of AI and data analytics therefore lies at the core of vehicle electrification — transforming data into actionable insights to enhance efficiency, promote sustainability, and elevate driver satisfaction within the EV ecosystem.
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Data collected by charging stations on power delivery, charging times, and payment transactions can optimise the performance of the charging network. Such data can guide stakeholders in making better decisions to manage station availability, prevent overcrowding, and reduce waiting times in charging stations.
Insights on peak times and charging frequencies allow the authorities to optimise charging station capabilities and mitigate the risk of underutilising stations across the city-state. Given LTA’s commitment to hit 60,000 EV charging points across Singapore by 2030, such data can even help map out optimal areas across Singapore for recharging points and prevent unnecessary infrastructure development in areas with low demand.
At the same time, drivers can leverage these insights to schedule charging times more effectively, alleviate strain on the power grid, prevent station congestion, and even reduce range anxiety. Adopting data storage solutions that leverage cutting-edge technologies, tailored to the software and AI demands, will underpin car electrification and deliver technology advances.
Big data can indeed be a gold mine from which we can create new value for the EV ecosystem. However, unlocking this potential requires overcoming the challenges posed by data silos and an antiquated technology infrastructure that impedes swift insights, stifles innovation, and complicates the value chain. The unique data storage and processing challenges posed by electric and hybrid vehicles require innovative solutions that enable high-speed data processing, minimise downtime, safeguard sensitive data, and offer the scalability and flexibility to manage the volume of data.
Embracing an all-EV future
We are now at a critical juncture in Singapore’s EV transition, where data holds the key to unlocking the full potential of electric mobility. Along with growing EV adoption, we need to modernise the data experience and find a better way to collect, clean, and process data to reduce time-to-insights as data from EVs, drivers, and charging stations flow at higher velocities.
A coalition of AI, data analytics, and a solid data framework can help democratise access to EVs and pave the way towards a connected, secure, energy-efficient, and driver-centric EV ecosystem in Singapore.
A combination of innovation and a whole-of-society approach that improves collaboration among industry stakeholders, policymakers, and technology innovators will accelerate sustainable EV adoption and turn Singapore’s electric mobility vision into reality.
Nathan Hall is the vice president for Asia Pacific and Japan at Pure Storage
