In this paper, the multi-fault diagnosis problem is investigated for series-connected lithium-ion battery packs based on an improved correlation coefficient method. Different from existing correlation-based fault diagnosis methods having difficulties in distinguishing between sensor faults and connection faults, a novel sensor topology is proposed to separate sensor faults from connection faults. Furthermore, to solve the problem of inconsistent correlation coefficients in different working states, an adaptive threshold mechanism is proposed. By combining the improved sensor topology and adaptive threshold mechanism, multi-fault detection and diagnosis can be realized. Subsequently, through different characteristics of the correlation coefficient and voltages, the types of sensor faults, such as the bias fault, scaling fault, drift fault, sticking state and noise, can be determined. Experiments prove the effectiveness and superiority of the proposed scheme. Note to Practitioners —This paper focuses on the multi-fault diagnosis of lithium-ion battery packs, aiming to enhance system robustness and longevity. The string-level redundancy topology structure greatly simplifies the fault diagnosis process without increasing the hardware cost and system complexity, which greatly reduces the calculation amount. With the adaptive threshold mechanism, the consistency of correlation coefficients in different working states is improved, so the accuracy of fault diagnosis and the robustness to different working states are increased. This paper uses four batteries in series to form a battery pack. In theory, the proposed method is equally effective when the number of cells in the pack rises. Thus, our multi-fault diagnosis method has great potential to be applied to electric vehicles and energy storage systems and adeptly addresses complex and dynamic operational environments. Our research has been validated in practical battery packs, yielding significant successes. By effectively identifying and addressing various faults, we have improved the overall performance and reliability of battery packs.

Electric vehicles (EVs) are designed to improve the efficiency of energy and prevent the environment from being polluted, when they are widely and reasonably used in the transport system. However, due to the feature of EV’s batteries, the charging problem plays an important role in the application of EVs. Fortunately, with the help of advanced technologies, charging stations powered by smart grid operators (SGOs) can easily and conveniently solve the problems and supply charging service to EV users. In this paper, we consider that EVs will be charged by charging station operators (CSOs) in heterogeneous networks (Hetnet), through which they can exchange the information with each other. Considering the trading relationship among EV users, CSOs, and SGOs, we design their own utility functions in Hetnet, where the demand uncertainty is taken into account. In order to maximize the profits, we formulate this charging problem as a four-stage Stackelberg game, through which the optimal strategy is studied and analyzed. In the Stackelberg game model, we theoretically prove and discuss the existence and uniqueness of the Stackelberg equilibrium (SE). Using the proposed iterative algorithm, the optimal solution can be obtained in the optimization problem. The performance of the strategy is shown in the simulation results. It is shown that the simulation results confirm the efficiency of the model in Hetnet.

This article proposes a novel data-driven approach for studying the stabilization of continuous-time delayed systems (CDSs) with both unknown model parameters and denial-of-service (DoS) attacks. Due to the effects of DoS attacks, such controlled CDSs can be viewed as a switched system with two modes: a stable mode during dormant intervals and an unstable one during attack intervals. Because of the switching character of the CDS with DoS attacks, some well-known data-driven control methods can not be used directly. To tackle this issue, a new relationship between the dormancy and activation periods of DoS attacks is built, which offers a more reasonable description of DoS attacks. Additionally, in the presence of measurement noise, a novel lemma (Lemma 3) is introduced to establish a data-based representation of CDSs using noisy measurement data. Without the need of explicit system parameter identification, stabilization criteria and control gain matrix are derived solely based on the input-state data. Finally, the effectiveness and good performance of the proposed method are illustrated through a numerical example and a power system.

This letter focuses on the design of a novel critical-area-based (CAB) stochastic denial-of-service (DoS) attack strategy aimed at diminishing the quality of remote state estimation in multi-area power systems. This attack strategy features two main characteristics: firstly, unlike most existing DoS attack models which typically overlook system information, the proposed CAB stochastic DoS attack strategy can selectively target critical areas of the power system, and the more severe impacts on system performance are expected. Secondly, the proposed attack strategy is stochastic, offering enhanced concealment compared to continuous or uniformly distributed DoS attack models. Furthermore, when the attacker faces energy constraints, an analytical relationship between the upper bound of the attack parameter and the expected total number of attacks is derived. Simulation results conducted on IEEE 39-bus and 118-bus systems validate that, compared to existing models, the proposed CAB stochastic DoS attack strategy induces more substantial disruptions in power system estimation quality, thus confirming its effectiveness from the attacker's perspective.

This article studies the finite-time synchronization (FTSyn) of neutral-type coupled systems (NTCSs) with controller failure (CF). Different from existing finite-time control methods for NTCSs, (wherein the time-varying delays should be involved in the controller), two kinds of simple and efficient controllers without any delay information are designed, which can simplify the controller design and system complexity. Specifically, a vector-based event-triggered mechanism (ETM) is utilized to save communication resource, and it can exclude Zeno effectively. Since the effect of CF is considered, the additional controllers do not work in some time domains, thus resulting in the classical finite-time stability theorem being invalid. By developing new analysis methods and constructing novel Lyapunov-Krasovskii functionals (LKFs), some sufficient criteria are obtained to assure the FTSyn. Note that the proposed LKFs are designed by introducing some free vectors, and as a result, the obtained criteria are termed by vector inequities, which are less conservative than the algebraic one. Finally, the effectiveness of the proposed scheme and design methods is demonstrated by two simulation examples.

Electric vehicles (EVs) are designed to improve the power efficiency as well as it prevents the environment from being polluted, and thus they are widely and reasonably used in the power market. Thanks to mobile charging stations (MCSs), it provides the charging service to EVs more easily with higher payoff and lower consumption, compared with the fixed charging stations (FCSs). In this paper, we propose a dynamic contract-based strategy to apply the secured charging service from MCS in Internet of things (IoTs), considering incomplete information of EV users. Firstly, considering this charging system composed of multiple EV users and MCSs, we design the utility function of each one, where non-contract power are supplied to EV users besides the power in contract items in IoTs. Then, in order to maximize MCS's profits, an optimization problem is formulated to obtain the optimal contract items satisfying EV users' power demand. Thirdly, the optimal solution of this problem is efficiently achieved through the presented iterative search algorithm, considering the different types of EV users with different contract items. Finally, simulation results validate the effectiveness of our proposal and each of them in this charging system can be benefited.