By
June 14, 2024
Fleet managers are constantly looking for ways to make their charging operations more efficient, cost-effective, eco-friendly, and secure.
Traditional fueling was simple. Drivers pull up to a pump, fill their tank, and they’re on their way.
With EVs, charging needs to be more coordinated and controlled. If an EV stays on charge for longer than needed, it may delay the charging of another vehicle leading to schedule disruptions.
For example, imagine two logistics EVs that are scheduled for back-to-back deliveries.
One takes 30 minutes longer to charge than expected. The first driver doesn’t report it, thinking it was just a minor delay. This creates a domino effect, delaying not only the second vehicle, but several other deliveries on that day.
And that’s not to mention the cost and eco implications of the extra power usage.
Coordinating complex charging schedules is impossible without careful oversight.
There are additional security challenges too. Fleets often charge EVs at various locations across a large depot. Even if the site is private, it’s important to securely authorize the driver or vehicle and reconcile EV charging bills for internal audits.
To achieve this, you need to know which EV is at which charger and for how long. That’s where smart charging technology and AI can help.
But before we look at AI-powered EV identification, let’s take a deeper look at some of the challenges that arise when using traditional methods.
There are three main types of traditional EV identification. Let’s take a look at how each one works and what the limitations are.
Many fleets have no authentication or EV identification measures in place at all. Under a setup like this, any driver can simply park up, plug-in, and the vehicle starts charging immediately.
This works okay for small, isolated, single-tenant sites where EV monitoring isn’t really relevant.
But for more complex settings, the no-authentication method falls down for the following reasons:
The beauty of RFID is its simplicity and cost-effectiveness.
A card or tag is used to authenticate drivers and their vehicles at charging stations. Each RFID card is assigned to an individual EV and an RFID chip may be attached to the vehicle key.
With broad compatibility across both AC and DC chargers, it’s a solid choice for fleet managers that tightens up security. There’s no doubt that RFID is a big step up from the previous no-authentication method.
However, there are a few potential downsides to using RFID technology for EV identification:
Plug-based or physical connector identification uses simple logic – match the plug to the vehicle type.
However, this simple system tends to only yield simplistic results, leading to a number of drawbacks:
One thing that all three traditional methods of EV identification have in common is a failure to provide real-time information about the vehicle or state of charge (SoC). Most commonly:
Without access to real-time data, it’s difficult to optimize your charging strategies, as you won’t have a clear picture of what is going on.
The rapid increase in EV adoption means that traditional identification methods are no longer good enough, for the following reasons:
Automatically identifying precise EV models and spec with AI engines is groundbreaking. It provides fleet managers with an adaptable, reliable, and scalable way to get reliable data and ensure accurate charger authorization.
AI algorithms use machine vision and pattern recognition to identify EVs through a network of cameras and sensors.
Deep learning models have been trained to analyze vehicle characteristics, such as shape, logo, and license plate. The AI engine cross references captured images with data in the model to identify the EV, using a variety of reference points to ensure accuracy.
You need to move with the times if you want to stay ahead in the rapidly evolving world of EV fleet management.
AI and machine learning technology is revolutionizing all aspects of life at the moment – and EV charging is no exception.
Outdated EV identification methods hold back efficiency gains and cost saving opportunities, so don’t fall into that trap.
Investing in AI-powered EV identification and smart charging software like Ampcontrol for EV fleets will future-proof your operations, enable rapid scaling, and raise your eco-credentials.
To find out more about how Ampcontrol can help you reach new levels of charging efficiency, get in touch and book a demo today.
Ampcontrol is a cloud-based software that seamlessly connects to charging networks, vehicles, fleet systems, and other software systems. No hardware needed, just a one-time integration.