Customize Consent Preferences

We use cookies to help you navigate efficiently and perform certain functions. You will find detailed information about all cookies under each consent category below.

The cookies that are categorised as "Necessary" are stored on your browser as they are essential for enabling the basic functionalities of the site.... 

Always Active

Necessary cookies are required to enable the basic features of this site, such as providing secure log-in or adjusting your consent preferences. These cookies do not store any personally identifiable data.

No cookies to display.

Functional cookies help perform certain functionalities like sharing the content of the website on social media platforms, collecting feedback, and other third-party features.

No cookies to display.

Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics such as the number of visitors, bounce rate, traffic source, etc.

No cookies to display.

Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.

No cookies to display.

Advertisement cookies are used to provide visitors with customized advertisements based on the pages you visited previously and to analyze the effectiveness of the ad campaigns.

No cookies to display.

AI, Electric Buses & the Art of Smart Charging: How Tenix Leads the Charge

by Torbjørn G. Krøvel, CEO Tenix

Picture a bustling city as dawn breaks: 500-1000 electric buses, each a cornerstone of sustainable public transport, await their morning routes. Behind the scenes, the charging process is anything but ordinary. It’s a masterpiece of precision orchestrated by Tenix CHARGE, an AI-powered system that ensures every bus receives the exact energy it needs—nothing wasted, nothing missed.

Torbjørn G. Krøvel, CEO, Tenix AG

At the heart of this innovation lies a Multilayer Perceptron (MLP), a sophisticated neural network trained on data from several hundred thousand trips to optimize charging for real-world conditions. This system doesn’t just manage energy; it transforms how fleets operate.

The Power of AI: How Tenix CHARGE Works

The MLP processes 28 unique parameters to deliver highly accurate charging predictions, with a precision of ±2%. These parameters include:

  • Route Topology: Accounting for energy demands on climbs, descents, and flat terrain.
  • Speed and Acceleration: Tracking driving patterns for better efficiency modeling.
  • Weather Conditions: Factoring in energy consumption variations from snow, rain, or heat.
  • Tire Pressure and Vehicle Load: Considering small but significant factors that affect energy use.
  • Time of Day and Traffic Patterns: Adapting predictions to the specific challenges of different hours and routes.

Training the AI Brain

The AI training process involves analyzing historical data from several hundred thousand trips, divided into smaller time windows that reflect energy use at specific moments during a journey. By layering these variables, the neural network learns to predict energy needs with remarkable precision. The result is smarter state-of-charge (SOC) predictions for each bus, ensuring optimal battery utilization without overcharging or wasting energy.

Real-World Impact of Smarter Charging

The real-world impact of Tenix CHARGE is profound. With precise SOC predictions, buses charge only as much as they need for their routes, reducing energy waste and operational costs. By integrating with platforms like Nordpool, charging schedules align with low-cost energy periods, saving operators up to 15% on energy expenses. Smarter charging also enhances fleet efficiency, allowing fewer buses to cover the same routes without compromising performance.

Driving Sustainability with Data

Beyond cost savings, the system contributes significantly to sustainability:

  • Reduced CO2 Emissions: 16–27% lower emissions compared to conventional charging methods.
  • Extended Battery Life: Smarter charging minimizes wear and tear, reducing the need for replacements.
  • Lower Environmental Footprint: Optimized operations mean fewer resources used over time.

Enabling the Future of Electric Mobility

By leveraging cutting-edge AI, Tenix CHARGE transforms electric fleet management into a data-driven science, delivering measurable benefits in cost efficiency, environmental sustainability, and operational precision. This approach underscores the critical role of intelligent software in enabling the widespread adoption of electric fleets, ensuring they remain a cornerstone of sustainable urban mobility.

This article was originally published by Tenix.

Tags

Visit Supplier

Visit Supplier Website

Contact Tenix

Address:

Saga Tenix AS
Lønningsvegen 47
5258 Blomsterdalen
Norway

Contact:

Call: +47 4777 0070

More News

Contact Tenix

Use the form to get in touch with Tenix directly to discuss any requirements you might have.










    We'd love to send you the latest news and information from the world of Bus-News. Please tick the box if you agree to receive them.

    For your peace of mind here is a link to our Privacy Policy.

    By submitting this form, you consent to allow Bus-News to store and process this information.