The Need
As electric vehicles (EVs) evolve toward multi-e-axle architectures, traditional energy management strategies fall short in optimizing power distribution and minimizing energy waste. Current systems lack the predictive intelligence to adapt to dynamic driving conditions, leading to suboptimal torque allocation, reduced efficiency, and limited range. There is a critical need for intelligent control systems that can anticipate road and traffic conditions to enhance energy efficiency, battery health, and overall vehicle performance.

The Technology
This technology, developed by OSU researchers, integrates V2X (Vehicle-to-Everything) and look-ahead information into a multi-e-axle electric powertrain controller. It uses predictive data—such as road grade, traffic signals, and speed limits—to generate an optimal torque profile. This profile is dynamically distributed across multiple electric motors to maximize efficiency and minimize power loss. Developed at CAR-OSU, the system includes a high-fidelity simulator and a control algorithm that operates motors in their highest efficiency zones, significantly reducing energy consumption and thermal losses.

Benefits/Advantages
• Reduces energy consumption
• Improves battery health through predictive torque control
• Enhances regenerative braking efficiency
• Minimizes motor stress and heat generation, extending component life
• Enables intelligent torque split for better traction and drivability