How AI & EVs Revolutionize Smart Commercial Fleets

The electric vehicle market has largely been focused on consumers, with companies such as Tesla, BMW, and Porsche marketing their vehicles to tech-savvy luxury car drivers.

However, software, logistic service providers, and charging infrastructure companies across the US, Europe, and Asia are increasingly helping commercial fleet managers transition to electric vehicles.

Commercial fleets are under pressure to cut their carbon emissions to meet government requirements and customer preferences. One obvious way they can do this is by deploying EVs.

EVs have the added benefit of having fewer mechanical parts and lower maintenance needs, but this requires careful management of vehicle routes and charging schedules.

The surprising result of one report? A survey by Bridgestone of 1,800 fleet managers across 15 countries found that 32% of them said artificial intelligence (AI) and machine learning will have the biggest impact on fleet management in the next five years, followed by EVs at 30%.

Techopedia explores where fleet management is going next.

Table of Contents Table of Contents

1. Key Takeaways
2. Data Analytics Change How Fleets Operate
3. How Electric Vehicles Benefit Commercial Fleets
4. How AI Can Optimize EV Fleet Operations
5. The Potential for Autonomous Vehicle Adoption
6. There Might Still Be Bumps in the Road
7. The Bottom Line
8. FAQs

Show Full Guide

Table of Contents

1. Key Takeaways
2. Data Analytics Change How Fleets Operate
3. How Electric Vehicles Benefit Commercial Fleets
Show Full Guide
4. How AI Can Optimize EV Fleet Operations
5. The Potential for Autonomous Vehicle Adoption
6. There Might Still Be Bumps in the Road
7. The Bottom Line
8. FAQs

Data Analytics Change How Fleets Operate

EVs and data analytics go hand in hand for fleet management — and fleet managers increasingly expect to increase their investment in digital fleet technologies over the next five years.

Some key statistics include:

Meanwhile, the vast majority of fleet managers — 85% — expect the number of electric and hybrid vehicles in their fleet to expand in the coming five years.

Jan-Maarten de Vries, President of Fleet Management Solutions at Bridgestone Mobility Solutions, said: “Artificial Intelligence and electric vehicles are transformative technologies that will continue to enhance fleet management.

“The move towards digital solutions, including AI, is no surprise to us and a clear indication of where the future of fleet management is headed.”

Why are fleet managers focused on AI and EVs? How can these innovations drive the future of fleet management?

How Electric Vehicles Benefit Commercial Fleets

Given each vehicle’s total cost of ownership (TCO) — from the purchase price to running costs such as fuel, tax, and insurance — EVs are becoming more cost-effective than internal combustion engine (ICE) vehicles for fleets. Governments providing tax incentives, subsidies, and grants can help companies save even more on costs.

The fleet managers in Bridgestone’s survey that say their fleet vehicle mix will evolve over the next few years expect their use of electric and hybrid vehicles will almost double from 37% currently to 63% by 2029.

EVs offer several advantages for commercial fleets:

• Lower operating costs: EVs are becoming popular among commercial fleets managers because they have fewer maintenance needs and electricity costs are typically lower than diesel or gasoline fuel costs, resulting in substantial cost savings over time.
• Environmental benefits: Fleet managers see EVs as a route to more sustainable operations. EVs produce zero tailpipe carbon dioxide emissions, helping them reduce their carbon footprint, meet environmental regulations, and attract customers who are increasingly looking to buy from sustainable companies.
• Energy management: Fleet managers can use data analytics to track each vehicle’s energy consumption to optimize performance. AI can also help to optimize charging schedules, so that vehicles charge during off-peak hours when electricity prices are lower to reduce energy costs.
• Longer operational use: As they have fewer moving components, EVs tend to experience less wear and tear than traditional vehicles — leading to a longer vehicle lifespan. Advancements in battery technology also continue to improve EV range and durability, while over-the-air software updates can enhance functionality without having to take vehicles to a physical garage.

How AI Can Optimize EV Fleet Operations

Data analytics can help fleet managers overcome range anxiety — the concern that EVs may not have enough battery power or access to charging stations to complete their routes.

Data embedded in onboard EV systems provides real-time information on battery health, charging levels, vehicle location, and driving patterns. AI algorithms can analyze this data to identify patterns and predict behavior, giving fleet managers a detailed view of each vehicle’s operations and actionable insights to inform their decision-making.

Here are some ways algorithms can help fleet managers avoid disruptions and plan their vehicles’ movements more effectively:

• Predictive maintenance: Machine learning algorithms can analyze onboard data to monitor battery health, identify potential issues and forecast when a vehicle will need maintenance. This reduces the number of unexpected breakdowns and minimizes downtime to keeping fleets running at full capacity.
• Route optimization: AI algorithms can analyze real-time and historical data to create optimized route plans based on delivery schedules, traffic conditions, battery status, charging station availability and vehicle efficiency. This means routes can be dynamically adjusted as needed to avoid delays that would deplete battery life and ensure vehicles are always close to a charging point.
• Charging optimization: AI can track vehicle usage and determine the best times and locations to charge, ensuring that fleets use charging stations during off-peak times as much as possible.
• Energy efficiency: AI can monitor vehicle battery levels and analyze data to optimize charging schedules and predict battery degradation. It can also provide drivers with real-time feedback on how to improve their vehicle’s battery efficiency, such as avoiding unnecessary idling, rapid acceleration and sudden braking.

The Potential for Autonomous Vehicle Adoption

Fully autonomous vehicles still need to reach commercialization, but the technology offers the potential to change fleet management once again.

AI enables self-driving vehicles to interpret information fed to them in real time from their cameras, sensors, and radar, perceive their surroundings, and learn from their environment. This can limit human error and improve vehicle safety while reducing labor costs.

Around half of fleet managers in Bridgestone’s survey pointed to enhanced driver and vehicle safety as the main reason to invest in fleet management technology.

There Might Still Be Bumps in the Road

While the integration of AI systems and EVs into commercial fleets offers clear benefits, companies face some challenges. The upfront cost of buying EVs and installing AI-powered systems or services can be high, so businesses need to weigh the initial costs against the anticipated long-term savings.

A sticking point for fleet managers in many places is the lagging development of sufficient charging infrastructure to meet EV demand, particularly for large fleets that operate over long distances.

It can also be challenging to ensure that drivers and fleet managers are well trained to operate and manage EVs with AI-enabled systems. These technologies promise increased efficiency, but they also require specialized knowledge to operate at their fullest potential.

The Bottom Line

EVs are becoming attractive to commercial fleet managers looking to improve sustainability and cut operating costs, while AI is optimizing fleet operations through predictive maintenance, route optimization, and energy efficiency.

Combining the two has the potential to change commercial transportation, both in theory and in reality. Bringing all of the information — both within the vehicle and outside the vehicle — directly to an AI, which is also aware of the company’s logistics plan as a whole, can move informed decision-making to a new level.

So, while there are still going to be drivers in the driver’s seat, there are likely to be co-drivers alongside them — and not the annoying kind who tut-tut and offer hindsight judgments while staring at a map.

FAQs