State of charge

About: State of charge is a research topic. Over the lifetime, 12013 publications have been published within this topic receiving 201419 citations. The topic is also known as: SoC & SOC.

Distributed Finite-Time Multiagent Control for DC Microgrids With Time Delays

Abstract: This paper proposes a novel distributed multi-agent finite-time control strategy with time delays for the state of charge balancing and voltage restoration in a dc microgrid with distributed battery energy storage systems. The delays can be different and theoretically unbounded for each battery system. Feedback linearization method is applied to convert the state of charge balancing and voltage restoration problems to double-integrator and single-integrator systems with input time delays, respectively. Then, the Artstein transformation is applied to reduce the time delayed systems to delay-free systems. Based on the reduced models, the finite-time control is modified to achieve the state of charge balancing and voltage restoration. Only the state of charge and its derivative and voltage information are required to be transmitted over a sparse communication network to generate the control signals. The finite-time Lyapunov method ensures accurate convergence and finite-time stability. The proposed secondary control strategy can be integrated with conventional primary droop control. The proposed control strategy is resilient to communication link failures and features plug-and-play capability. The performance is verified with an RTDS Technologies real-time digital simulator, using switching converter models and nonlinear lead-acid battery models.

Charge-Depleting Control Strategies and Fuel Optimization of Blended-Mode Plug-In Hybrid Electric Vehicles

Abstract: This paper investigates the fuel consumption minimization problem of a blended-mode plug-in hybrid electric vehicle (PHEV). A simplified mathematical model of the PHEV was constructed to obtain optimal solutions for depleting the battery to a given final state of charge (SOC) under constant vehicle speed. An optimal power strategy was constructed from theoretical analysis and simulation for constant speed cases and then applied to typical drive-cycle simulations for a middle-size plug-in sport utility vehicle in the Urban Dynamometer Driving Schedule, the U.S. Environmental Protection Agency US06 (Supplemental Federal Test Procedure), and the CR-City drive cycles. Simulation results indicate that the proposed control strategy is more efficient than other strategies of interest. Only the electric system loss characteristics, vehicle power demand, total battery energy, and trip distance are needed to implement the proposed control strategy in a PHEV. It does not rely on the detailed trip information other than the total trip distance. Therefore, it is possible to implement the control strategy in real time if the total trip distance is known before the trip.

SOC Estimation-Based Quasi-Sliding Mode Control for Cell Balancing in Lithium-Ion Battery Packs

Abstract: The successful and safe operation of a serially connected battery pack necessitates dynamic energy equalizing to adjust each cell's state of charge (SOC) to the same level, since there exists energy imbalance among its cells. Bidirectional Modified Cuk converters are utilized as the cell equalizers due to their advantages of integrated infrastructure and modular design. Distinguished from the literature, the maximum allowed cell equalizing current is designed to vary with the change of the battery pack's external current rather than a constant to avoid the cell's current exceeding its limitation. With adaptive quasi-sliding mode observers designed for the cells’ SOC estimation, a discrete-time quasi-sliding-mode-based strategy with saturated equalizing current constraints is proposed to have the converters work together efficiently to achieve the cells’ SOC equalization. As analyzed in mathematical proofs and shown in experimental results, the cells’ actual SOC differences can converge to a tolerant range around the origin in a relatively short time under the designed SOC estimation-based cell balancing method.