BATTERY STATE ESTIMATION FOR APPLICATIONS IN INTELLIGENT
                                        WAREHOUSES
       When it comes to AGVs (Automated Guide Vehicles) working in intelligent warehouse
systems it is necessary to take into account that the use of batteries may impact the performance
of the overall system. They need to be recharged or changed, and the time required to execute
these operations might interfere in the AGV availability. Therefore, it is necessary to carry out a
battery management procedure to ensure that the batteries have sufficient charges to perform the
desired tasks. This paper describes a method to estimate the Batteries State of Charge (SOC).
The estimated consumption is compared with the SOC obtained by the method. A series of
experiments using mini-robotic forklifts were performed to evaluate the method. The
experimental results have shown its effectiveness using resistive loads. This methodology
allowed estimating the battery consumption for a certain route of the mini-robotic forklift in the
warehouse and verifying the load capacity available for the mini-robotic forklift to accomplish a
task assigned by the warehouse routing system.

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Rt094

  • 1. BATTERY STATE ESTIMATION FOR APPLICATIONS IN INTELLIGENT WAREHOUSES When it comes to AGVs (Automated Guide Vehicles) working in intelligent warehouse systems it is necessary to take into account that the use of batteries may impact the performance of the overall system. They need to be recharged or changed, and the time required to execute these operations might interfere in the AGV availability. Therefore, it is necessary to carry out a battery management procedure to ensure that the batteries have sufficient charges to perform the desired tasks. This paper describes a method to estimate the Batteries State of Charge (SOC). The estimated consumption is compared with the SOC obtained by the method. A series of experiments using mini-robotic forklifts were performed to evaluate the method. The experimental results have shown its effectiveness using resistive loads. This methodology allowed estimating the battery consumption for a certain route of the mini-robotic forklift in the warehouse and verifying the load capacity available for the mini-robotic forklift to accomplish a task assigned by the warehouse routing system.