Summary: Battery technology is advancing rapidly as electrification expands across transportation, energy infrastructure and industrial sectors. From EV innovation to circular supply chains, several key trends are redefining energy storage. For engineers and energy professionals, understanding these developments is critical to building a resilient, low-carbon energy ecosystem.

Battery energy storage has become a foundational technology for electrified transportation, renewable energy integration and next-generation industrial systems. As the pace of innovation increases and the energy sector looks to meet net-zero goals, the battery energy storage market is predicted to more than double, climbing from US$51 billion in 2025 to US$106 billion in 2030.

With record investment and surging demand, keeping pace with battery system evolution is vital. These systems are not just components; they are essential infrastructure for the modern energy ecosystem.

Explore five key trends shaping the next generation of battery technology:

1. Accelerating Innovation for EV Batteries

Electric vehicles remain the primary catalyst for global battery consumption, surpassing the 1 terawatt-hour milestone in 2024. To illustrate this scale: One week of demand in 2024 equaled an entire year’s worth of demand from just a decade earlier. The International Energy Agency expected this demand to triple by 2030.

To meet this challenge, manufacturers are optimizing performance in four critical areas:

  • Energy density: Extending vehicle range
  • Durability: Maximizing life cycle performance
  • Manufacturing: Driving down cost-per-unit through efficiency 
  • Safety: Enhancing thermal management systems

In addition, integrating on-site storage with ultra-fast charging networks is becoming a standard design strategy to reduce grid strain while minimizing charge times.

2. Expansion of Grid-Scale Energy Storage

Grid-scale energy storage is among the fastest-growing applications in the field, fueled by the shift toward intermittent renewables. These systems support grid stability by responding to supply-demand fluctuations within milliseconds. Additionally, the massive power requirements of AI data centers have repositioned Battery Energy Storage Systems as mission-critical infrastructure.

The U.S. Energy Information Administration predicts record growth in generating capacity this year, with solar power representing 51% of new nationwide capacity.

As this sustainable energy comes online, engineers must be equipped to design and operate storage systems that integrate seamlessly with legacy infrastructure.

3. New Chemistries Beyond Lithium-Ion

While lithium-ion currently dominates, researchers are fast-tracking alternative chemistries to  improve cost and performance:

  • Solid-state batteries: By replacing liquid electrolytes with solid materials, these units promise higher energy density and superior safety.
  • Sodium-ion batteries: Utilizing abundant materials, sodium-ion offers a low-cost solution for grid-scale storage, where cost per kilowatt-hour is the deciding factor.
  • Structural batteries: These integrate directly into vehicles or aircraft frames, potentially reducing weight and increasing range.
  • Lithium-sulfur batteries: While still in the pre-commercial research phase, this chemistry is gaining traction for its reduced reliance on critical minerals.

4. The Rise of a Circular Battery Economy

Rapid growth brings sustainability into focus. The Ellen Macarthur Foundation warns of potential supply shortfalls for critical minerals by the mid-2030s. To meet demand, experts advocate for the circular battery economy to bolster supply chain resilience.

Key pillars of circularity include:

  • Advanced recycling technologies to recover high-value minerals
  • Second-life applications in which retired EV batteries are repurposed for stationary storage
  • Designing for recyclability from the initial engineering

This circular approach is a win-win, offering significant environmental benefits while lowering materials costs for manufacturers and end-users alike.

5. High-Performance and Specialized Applications

Electrification is moving into sectors once thought unreachable: aviation and shipping. As storage technology matures, we are seeing a shift toward high-powered mobility.

  • Aviation: Major aerospace manufacturers are actively flight-testing electric propulsion. 
  • Maritime: Studies suggest that electrifying up to 85% of cargo ships could be cost-effective by 2035, provided they cover 99% of annual trips and charge from a deeply decarbonized grid.

Knowledge To Power the Next Generation

To meet COP28 goals, global battery storage capacity must increase sevenfold by 2030. This milestone requires a workforce of skilled energy integrators who can design, deploy, and manage complex systems.

The Battery Energy Storage Technologies and Applications course program from IEEE offers a deep dive into these essential technologies. Developed in partnership with the IEEE Power & Energy Society, this program covers everything from system design and safety to emerging industrial applications.

  • Recognition: Earn professional development credits and a shareable digital badge. 
  • For organizations: Empower your team with expert-led battery energy storage training. Connect with an IEEE content specialist to begin your enrollment.

 

Artificial intelligence (AI) systems are evolving fast. However, ethical standards that ensure these systems don’t harm the public, such those that aim to prevent unintentional biases based on the data these systems are trained on, have been less quick to evolve. According to a global survey conducted by MIT Sloan Management Review, which polled over 1,000 executives, 82% of managers in organizations with at least USD $100 million in annual revenues agreed or strongly agreed that responsible AI (RAI) should be included in their top management agenda. At the same time, only 50% reported that RAI is a part of their top management’s agenda. 

How can organizations that develop or use artificial intelligence ensure RAI is not just an afterthought? A recent panel of global AI experts, organized by MIT Sloan Management Review and global consulting firm BCG, concluded with the following takeaways:

  • Leadership needs to understand why RAI is important to the organization’s strategy. Otherwise, RAI may never make it into the agendas of the organization’s major decision makers.
  • Determine whether RAI is part of your AI strategy or a part of your wider organizational goals, such as corporate responsibility. Without an understanding of this, leadership may not fully grasp that it should be integrated into their larger agenda.
  • Look at RAI as an urgent need that must be integrated now. Otherwise, you may miss valuable opportunities to prevent risk and harm down the line.

What are the Fundamental Principles of AI Ethics?

Understanding the core principles of AI is the first step to developing an effective AI standards framework. Such a framework should also align with an organization’s mission. It should also align with any regulations the organization may be affected by through its implementation of the AI system. According to TechTarget, the basic principles of ethical AI include:

  1. Fairness: The AI system does not contain biases and functions equally well for all groups 
  2. Accountability: The AI system has ways to identify who is responsible across different stages of the AI life cycle if something goes wrong. It also provides ways for humans to supervise and control the system
  3. Transparency: When the AI system makes a decision, it allows humans to understand why it came to that conclusion. This is essential for building trust
  4. Safety: The AI system is equipped with effective security controls

Incorporating These Principles into AI Systems

During an interview with Analytics India Magazine, Layak Singh, CEO of Artivatic AI, an insurance platform, said the company reduces biases in AI by defining the business problems it wants to solve while considering end users. They then configure data collection methods to be able to incorporate diverse perspectives.

“We also ensure that we clearly understand our training data, as this is where most biases are introduced and can be avoided,” Singh said. “With that aim, we also ensure an ML [machine learning] team that’s assorted as they ask dissimilar queries and thus interact with the AI models in various ways. This leads to identifying errors before the model is underway in production. It is the best manner to reduce bias both at the beginning and while retraining models.”

Additionally, there is a major focus on feedback as his company keeps feedback channels, such as forum discussions, open in order to run continual audits and upgrades.

Ensuring AI systems are ethical is becoming essential to building trust with clients and customers. Don’t wait until that trust is already broken— start developing an ethical AI standards framework today.

Incorporating AI Standards at Your Organization

An online five-course program, AI Standards: Roadmap for Ethical and Responsible Digital Environments, provides instructions for a comprehensive approach to creating ethical and responsible digital ecosystems. Contact an IEEE Content Specialist to learn more about how this program can benefit your organization.

Interested in getting access for yourself? Visit the IEEE Learning Network (ILN) today!

Resources

Krishna, Sri. (20 April 2022). Talking Ethical AI with Artivatic’s Layak Singh. India Analytics Magazine. 

Kiron, David, Renieris, Elizabeth, and Mills, Steven. (19 April 2022). Why Top Management Should Focus on Responsible AI. MIT Sloan Management Review.

Kompella, Kashyap. (1 April 2022). How AI ethics is the cornerstone of governance. TechTarget.