November 11, 2021
According to the Environmental Protection Agency (EPA), the U.S. transportation industry accounts for the most significant portion of total U.S. greenhouse gas (GHG) emissions (28 %). The medium-and heavy-duty truck sector causes 23 percent of those emissions.
The last years, fleet electrification has primarily focused on the light-duty vehicle (LDV) section. However, recent developments with medium and heavy-duty electric vehicles (MHDVs) point toward encouraging signs of future growth in that segment. But, what is essential for companies that decide to electrify their fleet? What should fleet operators keep in mind when planning the transition? Here you find three critical success factors.
Car breakdowns are the main cost driver for company fleets and can ruin a smooth business process for the fleet operator. Consequently, ensuring the high availability of the vehicles (avoid car failures) is one key goal for these enterprises.
More precisely, it's the moving components in regular gasoline or diesel engines that tend to fail over time and can include anything from the pistons to the belts. The great advantage of an electric car engine is that it has no moving parts, so these cannot break in the same manner. This makes EVs more predictable than fuel-based cars.
Since wearing parts can sometimes be the most expensive repairs on a car, owners of electric vehicles will find themselves saving large sums of money on repairs. That's not to say an electric car doesn't have parts that can fail, but these aren't found in the engine. Instead, they will be in other areas, such as the wheels or the brakes. Unfortunately, this is inevitable with every vehicle on the road.
So, what can fail in an electric car engine? Mostly, there are two possible points of failure on an electric car engine, and these are the battery and the connections. These can be extremely complex and will need specialized equipment to trace any defects. However, all big U.S., European, and Asian car companies (OEMs) have made massive progress in battery and electronic technologies. All major manufacturers (e.g., Tesla, Volkswagen, Toyota, and Ford) have shifted their strategic focus on electric cars and have addressed the weak spot well in the last years.
As EVs offer a lower cost per mile than ICE vehicles, enterprises are saving 50% or more in fuel and maintenance costs. These significantly lower fuel costs and the above mentioned smaller operations risks make electric fleets more cost-efficient. However, charging a high number of EVs at the same time can create spikes in demand for power and incur expensive "demand charges" from a utility. In addition to this, the fleet operators have to overview possible on-peak and off-peak kWh prices or even negotiate a more suitable energy contract with his energy retailer or energy supplier. In some states and countries, he might also work with an energy broker firm to optimize his energy purchase costs.
Therefore, having a well developed and proven technology for load management is vital. Firstly, pick networked charging stations that allow communication to the internet through Wifi, 3G, Zigbee, or similar. Networked EV charging solution delivers critical performance and maintenance information so fleet managers can anticipate and head-off potential problems. Secondly, use a networked cloud solution with a single view of all stations, capable of adding features over time. To ensure this, the operators should select a software system that is independent of charging hardware (vendor-neutral). Here, one should keep in mind that the charging station technology can be compared with the stage of smartphones ten years ago.
Local load management optimizations (often integrated into the EV charge point or a local controller) are an alternative to cloud-based controllers. However, we recommend using cloud-based solutions. Cloud solutions are often more stable and secure as they use various backup functionalities and servers. Moreover, optimization methods on cloud services are more scalable and robust than local ones. This is essential for the last section below.
Fleet managers often start by testing a small number of electric vehicles first, before continuously exchange combustion cars with EVs on a bigger scale. Each new electric van, truck, or car increases the complexity of charging the car and scheduling your fleet.
Connecting the two systems (fleet management software and EMS) in the optimization helps. By feeding the charging management software with dispatch information, the optimization becomes more precise. This includes information such as the expected leave time of the vehicle for the next delivery or the timestamp when multiple EV busses arrived at the depot. Most of the time, information is already available in the current fleet management system. If not, one can also add small affordable IoT devices to track, for example, GPS and battery data in real-time. The right algorithms and machine learning tools can then take over the math and control the charging schedules entirely to reduce costs and meet the program. Notably, once the enterprise needs the ability to handle growing demand for charging cycles, using a data-driven optimization is unavoidable.
Smart charging streamlines fueling and operations and delivers maximum vehicle uptime. However, the responsible staff should not lose control of the activities in a black box. Therefore, most advanced tools provide mature dashboards and control systems. The dispatcher can select options, prioritize specific vehicles or EV users, and add new rules to the decision-making process.
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.
Discover 9 common EV fleet charging mistakes and how to avoid or overcome them early in your transition to electric.
For the smooth operation of charging networks, regular testing of OCPP systems is needed. In this article, we provide an overview of OCPP is and why testing is a great way to maximize your options.