With advancing technology in recent years, AI in battery management and IoT battery monitoring will play significant roles in reshaping the way battery management is performed within material handling. By combining Artificial Intelligence (AI) and the Internet of Things (IoT), businesses can optimize their battery systems to combat these common challenges while maximizing their sustainability efforts.

The Challenges of Traditional Battery Management

Traditional battery management approaches have consistently experienced challenges such as inefficient monitoring methods, high maintenance costs, and frequent downtimes.

Historically, battery monitoring methods included periodic manual inspections, leaving room for errors to occur. Manual inspections can consist of inconsistent results and reporting, delayed responses to failing batteries, and is extremely time-consuming. Manual monitoring also lacks real-time data on battery health, which can lead to unexpected failures.

With the lack of real-time data, companies often take a reactive approach to battery maintenance instead of being proactive. This means repairs or replacements happen only after a noticeable decline or failure has occurred which results in high maintenance costs to fix the issues, putting a significant strain on operational budgets.

Poor battery management creates unexpected downtimes, which can become very costly to companies. These interruptions significantly reduce the amount of equipment that is available to continue production, hindering workflows and productivity, and costing companies additional expenses to ultimately repair or replace the failing batteries.

The Role of AI in Battery Management

With the use of AI algorithms, technicians will have a better understanding of battery performance as these algorithms will be able to predict battery health, optimize charging methods, and help extend battery life.

AI algorithms analyze both historical and real-time data from batteries to predict potential issues before they occur. This forecasted data helps to prevent failures as it provides information to identify early signs of degradation, overheating, or abnormal usage patterns. This data will allow technicians to schedule timely maintenance, helping to minimize downtime and avoid the high maintenance costs that are required to fix catastrophic failures.

AI-powered battery management also optimizes charging processes. These algorithms can determine the optimal charge duration and rate based on battery usage patterns and the environmental conditions they operate in. AI algorithms also prevent overcharging which can lead to heat buildup and lost capacity, reducing the battery’s lifecycle. AI algorithms can also contribute to energy efficiency efforts by scheduling charging during off-peak hours or when renewable energy is available, helping save energy and reduce operational costs.

IoT-Enabled Battery Monitoring

IoT-enabled battery systems will transform the way battery monitoring is performed by enhancing visibility on battery health and encouraging preventative maintenance.

With embedded IoT sensors, technicians can track parameters like voltage, temperature, and charge cycles to gain real-time data on battery health. These crucial insights and IoT-driven alerts will enable teams to take a proactive maintenance approach, addressing potential issues before they escalate, and ultimately reducing repair costs and improving reliability.

These remote battery diagnostics grant operators full insights into their battery’s performance, allowing them to monitor and adjust battery performance from anywhere as this data is transferred wirelessly to a central system or cloud-based platform.

Integration of AI and IoT in Material Handling Equipment

These technologies are currently being integrated into equipment such as forklifts, electric pallet jacks, and AGVs. Older vehicles can be retrofitted to include IoT sensors and AI-driven algorithm systems, or have external infrastructures installed like smart battery chargers and fleet management systems.

Integrating AI and IoT in the material handling industry will revolutionize fleet battery management and we will begin to see a significant impact on operations. With the help of AI algorithms providing predictive insights to battery health and IoT sensors tracking critical parameters and alerting techs of potential issues, downtimes will be greatly reduced, and battery management schedules will become streamlined. Companies will see an increase in their productivity, while reducing operational interruptions, costly maintenance repairs, and energy waste.

The Future of AI and IoT in Battery Management

AI and IoT will play an important role in the future of battery management, especially with emerging technologies and sustainability efforts.

Looking at industry trends and emerging technology, there will be advancements in wireless BMS (wBMS). Wireless BMS will eliminate the need for physical wiring and will instead include a wireless central control unit with sensor modules attached to each battery cell to collect individual cell data, reducing the weight on battery packs. The wireless control unit will then be able to transmit, utilize, and make informed decisions with the collected data.

We may also see the implementation of solid-state batteries, which use solid-state electrolytes instead of liquid or gel. With innovations made in the materials solid-state batteries use they can withstand more charge cycles, increasing their lifespan.

With the collection of real-time data, AI algorithms and IoT-connected chargers will be able to analyze charging schedules to charge equipment during off-peak hours and adjust energy based on demand predictions, allowing businesses to reduce costs and increase energy efficiency.

These technologies also have the ability to track batteries through their lifecycle to ensure use of their full potential to help increase recycling efforts, decreasing the overall waste and need for more raw materials. Repurposing used batteries in second-life applications that are less demanding will also help contribute to sustainability efforts.

Conclusion

AI and IoT are revolutionizing battery management in the material handling industry, addressing challenges like performance inefficiencies, unplanned downtime, and high maintenance costs. By integrating AI-powered battery management and IoT-enabled battery systems, businesses can optimize energy usage, extend battery life, and enhance sustainability.

At FSIP, we understand the importance and impact that automation and AI will have to the material handling industry. To help you keep up with those changing landscapes, we are dedicated to offering a variety of products to help with automated battery testing and real-time data collection.

FSIP’s Xtender Battery Regenerator is an all-in-one unit that discharges, desulfates, and recharges lead-acid batteries using patented Shark Pulse technology. Featuring remote monitoring capabilities, users can oversee the regeneration process and access detailed battery capacity reports remotely. This machine automates battery testing, helping with the service process and saving your business money.

The DisChargePlus is designed to test your battery’s remaining capacity. It can be used on 36 or 48-volt lead-acid or lithium-ion battery sets, offers programmable discharge rates, time, and shut-off voltage, and can operate without needing AC power.

The Smart Discharger is designed to automatically provide a graphical analysis of a battery’s remaining capacity. It discharges batteries at a controlled current of up to 200 amps on 12–96-volt battery packs and offers programmable discharge termination based on voltage reached, time elapsed, or capacity discharged.

Both the DisChargePlus Battery Discharger and Smart Discharger can be paired with our Battery Monitoring System (BMS) to have an automatic transfer of discharge data to your PC.

FSIP’s Battery Monitoring System (BMS) tracks individual cell health, providing critical data to optimize battery performance. By collecting and analyzing information on each cell, the BMS enables predictive maintenance and enhances overall battery efficiency.

The Delta Wireless 1kW Battery Charger is a lightweight and compact charger that works with lead-acid and lithium batteries. This charger provides contactless charging and is designed for AGVs/AMRs. Through CANopen and Ethernet connectivity, it can integrate into smart warehouses and systems to automate and view charging and charge data. The Delta Wireless also works in conjunction with our GREEN Series Industrial Battery Chargers.

Interested in learning more about these products? Contact our sales team today at sales@fsip.biz or 800-333-1194!