Mobility charge tool


Optimising charging points is already on the radar of city infrastructure planners, but what are the possibilities of smart electrification in the industrial sector?

Artificial intelligence (AI) will increasingly make it possible to plan the electrification of urban infrastructure so that the economic and environmental effects are comprehensively taken into account. AI may soon also be a viable option for industrial operators aiming to reduce emissions during operation. Could electrification even be the next industrial market disruption?

Although the popularity of electric cars has weakened for a while due to higher electricity prices and rising interest rates, the demand trend is still rising, both globally and in Finland. This trend of the electrification of the car fleet is driven, for example, by the EU’s decision to attempt to end the sale of new combustion engine vehicles by 2035. It is therefore no wonder that the optimisation of the electrification strategy is strongly on the agenda in the planning of urban charging point infrastructure.

“Currently , the infrastructure of electric vehicles is still poorly optimised in several countries, which in turn leads to a poor customer experience and low profitability – both of these are trends that strongly inhibit the introduction of electric cars,Kimmo Pekkola from Deloitte says. 

However, electrification is becoming smarter. The Mobility Charge tool developed by Deloitte’s Future of Mobility Solution Centre enables demand- and supply-based decision-making, which in turn allows a company or a provider of charging points (for example, a real estate investment company) to plan the implementation of the optimal charging infrastructure according to the development of the market.

"The [Mobility Charge]  tool utilises big data and takes into account several requirements at the same time, such as the behaviour of individuals, infrastructure limitations and competing charging options. With the help of scenarios, the provider can optimise an investment, for example, in terms of time, location and capacity. The everyday life and “charging anxiety” of the consumer driving an electric car will become easier, the planning of the charging service provider will be sharpened, profitability will improve, and, at the same time, the adequacy and efficiency of the electricity network will be improved,”  Dmitry Khramov from Deloitte states.

Is electrification with AI the solution to reducing industrial emissions?

Reaching the emission targets is not only an issue of meeting the regulator’s requirements, it is also an important part of the industry’s competitiveness. Industrial players that are especially focused on transport, cargo-handling and equipment solutions are thinking about reducing emissions created during operation and are striving to move from internal combustion engine solutions to an electrified equipment base.

“The mobile heavy machines of industry, and the mobile cranes and cargo movers of the terminals could also operate with electricity more often than at present. It is a different use case compared with electric cars, so naturally the use of electricity and its consequences are also very different,” Kimmo Pekkola poits out.

For example, in a terminal environment, it is important to ensure that industrial operations are not disrupted by electrification. At the same time, attention is drawn to the overall solution consisting of individual devices, possibly devices from several suppliers, and its optimal operation. In addition to operational activities, this may affect the purchasing behaviour of B2B decision makers. When, in addition to the devices, the charging and control functions that support them change, sellers must be able to influence the customer’s procurement process at an earlier stage.

“In terms of efficient and smooth operation, an optimised charging infrastructure implementation plan, including the placement of charging points, is a very central starting point. Other clear benefits are the forecasting of cost benefits with the help of data (for example, on an annual basis), at which point electrification pays for itself and starts to generate profit,” says Dmitry Khromov.

The possibilities of the Mobility Charge tool in a nutshell

  • Demand forecasting: Estimating the charging needs for electric vehicles and devices based on multi-parameter local deployment modelling.
  • Infrastructure planning: Defining charging points and distribution deployment planning in order to maximise usage.
  • Impact simulation: Simulating customer, financial and environmental impacts based on the proposed infrastructure plan.
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