This review provides an overview of new strategies to address the current challenges of automotive battery systems: Intelligent Battery Systems. They have the potential to make battery systems more performant and future-proof for coming generations of electric vehicles. The essential features of Intelligent Battery Systems are the accurate and robust determination of cell individual states and the ability to control the current of each cell by reconfiguration. They enable high-level functions like fault diagnostics, multi-objective balancing strategies, multilevel inverters, and hybrid energy storage systems. State of the art and recent advances in these topics are compiled and critically discussed in this article. A comprising, critical discussion of the implementation aspects of Intelligent Battery Systems complements the review. We touch on sensing, battery topologies and management, switching elements, communication architecture, and impact on the single-cell. This review contributes to transferring the best technologies from research to product development.

Due to their high efficiency and advanced battery management capability, cascaded multilevel inverters are an exciting option for battery electric powertrains. A promising, new and highly efficient cascaded multilevel inverter is the Parallel Enhanced Commutation Integrated Nested Multilevel Inverter. The inverter, with four semiconductor switches per submodule, can reconfigure individual battery cells in series and parallel and generate positive and negative phase voltages in regular four-quadrant operation. Therefore, emerging degrees of freedom in battery management and inverter operation must be managed and mapped into a specific Switching State for every switch. As controlling the high number of switches is safety-relevant, this publication profoundly explains the inverter’s functionality. We introduce a Switching Function that accepts easy-to-understand functional states as input, simplifying research on higher-level control algorithms and advanced single-cell battery-management capabilities. As the Switching Function guarantees safe operation and the correct contribution of every cell to the overall functionality of the inverter, it enables researchers to confidently use and thereby accelerate research on the promising new topology. The method we describe is fast, simple, deterministic and designed to convert setpoint specifications into an executable Switching Pattern. We prove that our Switching Function is operable on an FPGA with a twenty-kilohertz setpoint update operating a 17-level inverter.

Battery system engineers face the challenge of balancing competing requirements regarding performance, maintainability, sustainability, safety, and cost—especially in the automotive industry. IBS potentially offer a solution with fewer trade-offs. They feature a battery management system with advanced sensing and data analysis capabilities that facilitate improved battery monitoring and operation. Reconfigurable energy storage units enable sophisticated operating strategies, including complete cell state control, full energy content utilization, and a measured response to faults. This article presents the design, development, and operation of a full-scale intelligent battery system prototype comprising 324 automotive lithium-ion cells with a nominal voltage of 400$\mathrm{V}$. The system exhibits a modular single cell architecture and an advanced centralized battery management system. We detail the system architecture, hardware and software component design, and system integration. Initial tests demonstrate the battery’s operability, extended functionality, and enhanced safety. Our analysis shows that the additional losses introduced by reconfigurability are more than offset by the benefits of full energy utilization—even for new cells, with increasing advantage as aging progresses. The results underscore the potential of intelligent battery systems and motivate further research and development toward economic assessment and industrial adoption.

Cascaded multilevel inverters constitute a promising system concept for battery electric powertrains due to their high efficiency, low harmonic distortion, and advanced battery management capabilities. This study presents a novel electro-thermal simulation framework for the symmetrical Parallel Enhanced Commutation Integrated Nested (PECIN) multilevel inverter. The proposed model employs a control-oriented approach that enables the development and evaluation of advanced inverter and battery control algorithms, which exploit the extensive series-parallel reconfiguration capabilities of the PECIN topology. The framework is based on electrical and thermal equivalent circuit models to capture physical behavior and cross-domain interactions. Electrical network analysis employs algorithms that iterate over each phase-arm network, replacing high-dimensional matrix inversions and thereby enhancing computational efficiency. The overall model is readily adaptable to various system configurations, including different AC and DC charging modes, and scalable with respect to the number of submodules and phases. Simulation results for a 31-level multilevel inverter in a three-phase AC charging configuration demonstrate the model’s operational capabilities. Execution time analysis shows that the current distribution calculation is the key contributor to computational effort as the number of submodules increases, resulting in a quadratic growth of the overall computational time.