For vehicle-to-grid (V2G) frequency regulation services, we propose an aggregator that makes efficient use of the distributed power electric vehicles to produce desired grid-scale power. The cost arising from battery charging and revenue obtained by providing are investigated represented mathematically. Some design considerations also discussed together with practical constraints such as energy restriction batteries. function enables us construct optimization problem. Based on developed...

This paper presents a new adaptive sliding-mode control (ASMC) scheme that uses the time-delay estimation (TDE) technique, then applies to robot manipulators. The proposed ASMC law achieve good tracking performance with small chattering effect. considers an arbitrarily vicinity of sliding manifold, in which derivatives gains are inversely proportional variables. Such provides remarkably fast adaptation and reduction near manifold. To yield desirable closed-loop poles simplify complicated...

It is essential to estimate how much power can be delivered from vehicles grid, called achievable capacity (APC), for practical vehicle-to-grid (V2G) services. We propose a method of estimating the APC in probabilistic manner. Its probability distribution obtained normal approximation binomial distribution, and hence represented with two parameters, i.e., mean covariance. Based on APC, we calculate that V2G regulation providers (or aggregators) are contracted provide grid operators with,...

This paper presents a practical adaptive time-delay control scheme (ATDC) and then applies it to robot manipulators. The proposed ATDC uses time-delayed signal cancel complex nonlinear dynamics disturbances, hence provide simple structure. law of the is developed adjust gains appropriately while in operation achieve good tracking performance with tolerant fluctuation fast convergence speed. Such are shown have an effect adding auxiliary conventional (TDC). Moreover, includes typical...

As artificial intelligence (AI) technologies have advanced, neural network-based aging estimation has been extensively studied for lithium-ion batteries. Its performance also steadily enhanced with sophisticated network designs and machine learning skills. However, utilizing well-designed AI-based estimators needs more research. This study shows that the same estimator performs differently depending on input current signal. article proposes a reinforcement (RL)-based framework digital twin...

This paper presents a widely adaptive time-delayed control (WATDC) without imposing any restrictions on allowable gains to make the most of advantages (TDC) and, then, applies WATDC robot manipulators. Since proposed can provide arbitrarily high by using time-varying bounds estimation errors, it has room for improving tracking performance and robustness existing stabilizing TDCs that have narrow range depending system parameters comprising inertia manipulator. Furthermore, employs fast law...

An economic feasibility study of vehicle-to-grid (V2G) frequency regulation is performed in consideration battery wear. Usually, a transaction for made terms power capacity while the battery-wear proceeds proportion to absolute amount energy transferred. In order relate two quantities, we first estimate transferred contracted capacity, and hence income, by analyzing actual signals transactions. On other hand, transferrable during life cycle estimated some pervasive specifications electric...

An electrochemical lithium-ion battery model is well known to be suited for effectively describing the microstructure evolution in charging and discharging processes of a with practically realizable complexity. This paper presents neural network-based parameter estimation scheme identify parameters an near-optimal real-time manner order consistently observe states batteries. The network first trained learn dynamics model, then, it applied estimate available finite-time measurements voltage,...

An economic assessment of the vehicle-to-grid (V2G) frequency regulation is performed regarding battery degradation. To generalize results, we utilize requirements electric vehicle and plug-in hybrid prepared by USABC - energy storage division consortium three major U. S. automakers. During assessment, actual signal analyzed to estimate amount transferred for V2G regulation. The profits are then calculated compared with prices assess feasibility In order match end-of-life criterion in...

State of health (SOH) is a key issue for saving cost and guaranteeing safety while using rechargeable battery. Therefore, numerous studies on SOH estimation have been conducted intensively. However, most the need experimental data whole lifetime battery, adopt standard charge/discharge pattern that does not reflect real world driving pattern. For these reasons, it suitable to apply results into battery management system (BMS) an EV. In this paper, practical classification scheme based...

Internode line impedance values are essential information for achieving coordinated voltage regulation with distributed energy devices. However, in a low-voltage distribution system, these difficult to acquire, especially when the devices installed an ad hoc manner by individual users. This paper proposes novel method automated estimation based on practically available parameters at terminal nodes. The measure and transmit host device. Then, device estimates impedances its model collected...

This paper proposes a new adaptive law for sliding mode control (SMC) scheme to achieve the effective switching gain tuning near surface. The proposed makes gains rapidly and effectively decrease surface provide well-functioning adaptation while avoiding sign changes caused by excessive adaptation. Such an mechanism contributes chattering reduction fast of without temporary large tracking errors. SMC (ASMC) works together with time-delay controller (TDC) more practical implementation based...

In order to accurately estimate the state of health (SOH) a Li-ion battery, reference performance test (RPT) needs be conducted between several charging/discharging cycles for obtaining accurate data concerning battery capacity and degradation. However, it is not practical perform RPTs frequently because they are time-consuming expensive; moreover, undergoes unnecessary degradation during operations. Therefore, should performed as infrequently possible. this paper, neural network-based SOH...

In this article, we propose an innovative model-free control (MFC) algorithm using adaptive model uncertainty estimator (AMUE) that provides stable torque input while allowing more precise control, even in the presence of instantaneous disturbances, such as friction, payload, or trajectory changes. Unlike traditional time-delay estimation (TDE)-based controllers directly use one-sample delayed signals to estimate unmodeled dynamics and uncertainties, proposed achieves better tracking...

As lithium-ion batteries age, the lithium inventory and active materials are gradually lost, limiting their lifespan. The stoichiometric range, which refers to operable range of amount in electrode, has been considered a representative comprehensive indicator for predicting aging process. For efficient safe use batteries, cathode anode ranges should be identified as accurately possible. Accordingly, because identification accuracy depends on input signals system operating conditions,...