5 Reasons Why Integrated Predictive BMS Can Help OEMs Reduce Battery Recalls
Imagine how disheartening it is to recall your vehicles just because of their poor battery management system (BMS). Firstly, you have to bear the loss, and secondly, your brand reputation has to face a sudden downfall. It’s the moment when you need to be smarter by integrating predictive analytics solutions into your connected vehicles’ batteries.
In this blog post, we’ll be exploring 5 evident reasons why you should go for predictive battery analytics solutions. But before that, let us share a few cases of battery failure when it wasn’t monitored.
What happens when the BMS in the connected vehicle isn’t monitored?
There are live examples of poorly managed batteries in electric vehicles which led to vehicle recalls. One of the incidents is from the disaster that happened due to faulty batteries in the OLA scooters.
In one case, a man and his daughter died after the OLA scooter caught fire just because of a poor battery management system.
Another example is in the case of Volkswagen, where several customers complained about the battery failure in their cars. A customer complained about the inconvenience he had to face after finding his car’s battery to be dead just by keeping the car parked for a day or two.
This situation would’ve occurred if the battery had an integrated monitor to predict the battery’s health. Let’s find out some other reasons for switching to predictive battery analytics solutions.
5 Evident Reasons Why Should OEMs Integrate Predictive Battery Analytics Solutions Into Vehicles
1. Helps In Reducing The Required Downtime In Equipment Maintenance
The biggest challenge that occurs while managing batteries in electric vehicles is the time consumed in fixing faulty battery equipment. But you can pass across this hurdle by integrating predictive analytics solutions into your EVs.
One good thing about predictive battery analytics is the early warning notification of equipment issues months before failure. Consequently, this helps OEMs and end-users to reduce vehicle downtime by avoiding time-consuming repairs.
With real-time monitoring and data-driven battery maintenance software, you can warn the end-user about upcoming troubles in the vehicle. This way, you can predict the problems and fix them beforehand.
2. Aims To Chuck Off Faulty Cells
Faulty cells are one of the main reasons behind the hazardous accidents caused due to battery failures. So, the best way to avoid this situation is to chuck off the faulty cells from your vehicle’s battery. It’s possible by monitoring the allowed current into each cell at the time of charging the battery.
While manufacturing a battery, you need massive investment in keeping cells as uniform as possible. And to achieve this accuracy in the uniformity of cells is a hard nut to crack.
However, if you have granular data on individual cells, you can easily predict the battery lifespan through battery diagnostics software. Besides that, this predictive analytics software can also help you choose suitable cells and develop better batteries in the pre-production stage.
3. Enhances overall battery progress and sustainability
Predictive battery analytics in vehicles can also enhance your overall battery progress and sustainability. The EV batteries already hold a zero-emission future where creating a robust battery management system will be like a cherry on top.
Moreover, the used cases of telematics data in EV batteries offer the following benefits:
Increased Operational Efficiency
Reduction in compressed air consumption
Forecasted system issues like wasteful leaks
4. Ensures That There is Minimal Loss In Productive Hours
Unplanned maintenance of EV batteries can lead to a substantial loss in production hours. Here is where you need regular monitoring and analysis of your EV batteries' health. Predictive analytics lets you replace the faulty components of the battery ahead of failure. Thus, you can minimize the productive hours lost to maintenance.
This technology will further provide a new approach to battery management solutions via condition-based maintenance. As a result, you will easily be able to prevent unnecessary maintenance labor.
5. Prevents Unnecessary expenses in sudden maintenance and spare parts replacement
Several times random battery failures in EVs can add to the miscellaneous expenses of the companies who use them. This situation can disturb their monthly or yearly budget. But if the end-users get to know glitches in their EV batteries beforehand, they can bear the minor maintenance expenses.
An IoT-integrated battery management system notifies the users to repair their batteries if there are any faults. It’s definitely less expensive than the spare parts that one is actually forced to replace due to sudden battery explosions or failures.
How Is Zeliot Helping OEMs to Adopt A Robust & Predictive BMS for Minimizing Battery Recalls?
Zeliot, a platform player in the vehicle telematics industry, brings in robust predictive battery analytics solutions to combat battery failures. Through forecasted battery analytics, they let OEMs and end users track the conditions of the EV batteries. So, it helps the users to get the estimation of the total life cycle of each cell.
Enlisted below are some of the offerings by Zeliot:
ECU flashing and Over-the-air remote diagnostics for reducing the need of getting the vehicles back to the dealership to update firmware
Provide solutions for servicing the vehicle remotely along with the integration of dynamic RSA services to ensure data security
Smooth updating of BMS firmware and remote battery diagnostics via Zeliot’s robust platform
An effective Battery-as-a-Service business model to enable custom solutions for each vehicle
Wrapping it up:
Indeed, in the world of disagreements, holistic predictive battery analytics will act as a fair arbitrator by offering a reliable database.
Preventive actions like ECU flashing and over-the-air remote diagnostics will lower the chances of technical issues that cause disruption. As a result, it will be easier to replace the defective modules in advance.
Are you ready to integrate predictive BMS into your EVs? Let’s connect!