Lithium-ion batteries (LIBs) are widely used in the fields of consumer electronics, new energy vehicles, and grid energy storage due to their high energy density and long cycle life. However, how to effectively evaluate the State of Charge (SOC), State of Health (SOH), and overcharging behavior of batteries has become a key issue in improving battery safety and lifespan. Acoustic sensing technology, as an advanced non-destructive monitoring method, achieves real-time monitoring of the internal state of batteries and accurate evaluation of key parameters through ultrasonic testing technology and acoustic emission technology. This article systematically reviews the research progress of acoustic sensing technology in SOC, SOH, and overcharge behavior evaluation of LIBs, analyzes its working principle and application advantages, and explores future optimization directions and industrialization prospects. Acoustic sensing technology provides important support for building efficient and safe battery management systems.

The adaptive tracking control strategy is investigated for a class of multi-input and multi-output pure-feedback nonlinear delayed systems with unknown dead-zone inputs. This problem is challenging due to the existence of unknown dead zones, time-varying delays and unavoidable state variables. By constructing fuzzy approximators and state observers, the difficulties from unknown nonlinearities and unavailable state variables are surmounted, respectively. Lyapunov–Krasovskii functions are introduced to deal with the time-varying delays. The adaptive controllers are designed by a backstepping method and adaptive technique so that the closed-loop systems remain stable and the target signals can be tracked within a small error as well. At last, two examples are provided to show the effectiveness of the proposed scheme.

This paper investigates observer-based adaptive fuzzy control for a class of delayed nonlinear systems in pure-feedback form. We first proposed a linear observer to get the estimation of the system's state. And then utilise fuzzy logic systems to model those nonlinearities. Further, adaptive fuzzy approach and backstepping technique are combined to develop the desired controller via Lyapunov analysis. The suggested adaptive fuzzy control scheme ensures that all the signals of the resulting nonlinear system converge to a small neighbourhood of the origin. Then a real simulation is used to illustrated the effectiveness of our results.

In this paper, an adaptive control is discussed for the synchronous generator which is connected to a single machine infinite bus system. By using Lyapunov stability theory and backstepping technique, the excitation controller is proposed to stabilize the resulting systems. Fuzzy logic systems are employed to identify the unknown nonlinearities. Finally, simulation results illustrate the effectiveness of our results.