The Importance of Battery Life-Cycle Innovation in Electric Vehicles




The automotive industry has been progressively transitioning to electric vehicles (EVs), which is likely to shake up market share and company profits. Success and performance will be based on a different set of technologies with new challenges and evolving consumer considerations. New models will have varying degrees of range, acceleration, cost, and functionality. The winners in this EV race will best adapt to customer needs and quickly deliver vehicles accordingly. However, even in this complex and hypercompetitive environment, there is a single dependency that will enable manufacturers to have a truly competitive advantage: battery innovation.

Read related articles in this issue of the NI Automotive Journal to learn more about the latest testing trends and innovations in the automotive industry.

A Race to Improve EV Battery Design &

The specs of EVs will be tightly correlated to this one component: the battery. Battery design, production, and life span will play a significant role in the success of any given model. Consider the following critical dependencies:

  • Recharge time
  • Impact of charge/discharge cycles
  • Consistency of electrical output
  • Manufacturing cost
  • Safety record
  • Temperature extremes

Evaluation of these attributes must occur again and again, pushing manufacturers to continually innovate to create the most compelling automobile. The winner in the long run will not be the vendor who creates the best battery technology once. It will be the vendor who best implements a company culture around battery innovation, enables a platform for rapid design, and embraces data to accelerate and enhance design cycles.

Fueled by the market factors and inherent application challenges, NI is taking a data-centric approach to battery innovation. Today, that starts in design and validation. R&D teams are finding new ways to manufacture EV batteries, and the data generated by these projects is vital. However, secure and timely access to this data across multiple sources and locations is difficult. Complexities with data formats, test procedures, storage locations, database schemas, and more make managing this valuable data a project of its own.

NI provides a comprehensive solution to address this challenge built on SystemLink™ software. This central platform simplifies the management of battery data by connecting to all data-generating sources to ingest and transform data into a known location with a set format and schema. The connectivity and data gateway create an extensible architecture to easily connect to existing and new validation labs. Then, a complete suite of battery awareness tools allows that data to be visualized and analyzed by the right people at the right time. With NI, manufacturers can standardize and automate their approach to battery data, which allows them to develop better battery technologies faster and at lower costs.

Diagram of the hardware and software components of the NI battery validation analytics solution.

FIGURE 01: NI battery analytics applications for battery validation

EV battery manufacturers then scale those designs into high-volume manufacturing, where focus shifts to process repeatability and accuracy. This process means achieving profitable production at scale and--more importantly--ensuring safe and reliable batteries are delivered to market. With millions of units to monitor and zero margin for error, the attention once again shifts to data.

From cell to module, pack, and chassis, the batteries create a valuable stream of data. This product-centric data taken directly from the batteries is the best representation of the health and stability of the production process. To extract that value, the data must be collected, harmonized, and analyzed effectively. Like in the validation space, NI also has a Battery Production solution that can extract this data, combine it with other sources (like MES or ERP systems), and generate meaningful insights about the production process and the battery design itself. These insights can support an array of data-driven or even automated decisions that will improve operational and business KPIs. With advancements in video processing and machine learning, this data is not limited to just test and measurement parametric results, but can even include camera images, like those used to inspect weld quality.

Diagram showing how battery production across cell, module, pack, and chassis map to the steps in the battery analytics process.

FIGURE 02: NI Battery Analytics Applications for Battery Production

Today, solutions in validation and production are available, but there is significant room to grow. Manufacturers who realize the importance of harnessing their battery lifecycle data and begin to implement infrastructure to extract that data now will have an advantage as the EV market matures. Getting ahead of the game as these technologies are developed will provide the base platform and company culture to drive battery innovation and allow manufacturers to leverage historical data to improve battery design. These companies will be positioned to deliver continual innovation on battery designs that are better than the competition.