Perfect Charging

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Perfect Charging

Efficient intralogistics thanks to digital networking of the charging infrastructure

Product

9/1/2021 / Wels
Utilize data from your battery chargers and secure a decisive competitive advantage. Thanks to digital networking of the charging infrastructure, you benefit from unprecedented transparency and can thus increase the efficiency of your intralogistics.
Man using Charge & Connect to monitor the performance of the charging infrastructure.

Minimize downtime

A decisive factor for economic efficiency in intralogistics is ensuring maximum availability of systems and forklift trucks. Downtimes of the forklift truck fleet cause high costs and drastically reduce the own productivity. Digital networking of the charging technology can make an important contribution to increasing the availability of the forklift truck fleet..

Continuous monitoring of the charging infrastructure

With our software solution Charge & Connect, it is possible to digitally link your forklift truck charging stations. A clear dashboard creates transparency with regard to all relevant charging data. Thanks to this continuous monitoring of your chargers, you can reduce downtimes of your forklift truck fleet to a minimum. In addition, application errors can be detected promptly and avoided in the future.

Push notification in real time

To enable you to react as quickly as possible when problems arise in the charging infrastructure, it is crucial to be alerted to misbehavior at an early stage. Our digital networking solution Charge & Connect sends automated push notifications in the event of anomalies in your charging infrastructure. You receive a detailed error description with associated step-by-step troubleshooting instructions. This means you are alerted to faults at an early stage and maintain an overview - even without being on site yourself.

Battery life extension

Above all, extending battery life is an important cost factor for many companies. The uneven utilization of the individual batteries leads to incomplete charging processes. On the one hand, this reduces the operating time of the forklift trucks and, on the other, leads to losses in battery life and, in turn, to higher costs.

Finding the cooled and fully charged battery made easy

Our proven battery management system "Cool Battery Guide (CBG)" helps you improve the utilization of your battery pool - and thus extend the service life of your traction batteries. The Cool Battery Guide can now also be used digitally via our Charge & Connect software. It can be easily activated with just a few clicks in the dashboard. Based on the processed signals of the chargers, you now always have the longest fully charged and thus the coolest battery in view.  A blue illuminated LED strip on the charger intuitively guides your employees to the battery that is ready for use.

Savings potential due to longer battery life

The Cool Battery Guide ensures even utilization of the battery pool. In addition, the Ri charging process of our Selectiva 4.0 chargers ensures energy-efficient charging that is gentle on the battery. Battery life can thus be increased by up to 15%. The associated savings per year are illustrated by the following example:

Voltage (V)

Ampere hour (Ah)

Quantity

Cost per battery

Savings due to the increase of battery life (per year)

 24 375 28 € 827,00 € 604,07
 48 750 24 € 2.760,00 € 1.637,22

Savings by increasing battery life after one year: € 2.561,63

Savings by increasing battery life after five years: € 12.808,17

 

Avoidance of peak loads

For many industrial companies, load peaks cause high electricity costs, which is why a reduction of these peaks leads directly to cost savings. Digital networking of the charging infrastructure can be used to avoid such load peaks.

Do you know the AC power draw of your charging infrastructure incl. min. and max. value of the last 24 hours? In the Charge & Connect dashboard, this value is visible at a glance. Through the long-term display of the power drawn by the chargers, you can easily see whether and at what times there are expensive load peaks. Based on this data, measures and optimization steps can be initiated to reduce energy costs.

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