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This paper is concerned with the secure estimation problem for the state of charge of Lithium-ion batteries subject to malicious attacks during the data transmission from sensors to cloud-based battery management system terminal. First, the second-order resistance-capacitance equivalent circuit model, whose parameters are identified by Kalman filter in an off-line manner, is introduced to describe the internal dynamics of lithium-ion batteries. Then, by applying the $\chi ^{2}$ detection mechanism, real-time malicious attacks are first detected and then a secure estimator is designed to suppress the influence of attacks on the estimation performance. An upper bound of the filtering error covariance is determined by solving certain coupled Riccati-like equations, and the filter parameter is obtained by minimizing such an upper bound at each time step. Finally, the validity of the proposed attack detection approach and the effectiveness of the developed estimation scheme are verified by experiment results under Federal Urban Driving Schedule condition. [ABSTRACT FROM AUTHOR]

To increase lifespan and optimize capacity utilization of lithium-ion (Li-ion) battery, it is imperative to predict its states accurately. This paper primarily focuses on offering an improved solution for estimating one of the most important battery states known as state of charge (SOC). After extensive analysis of the current state-of-the-art methods, we propose a new adaptive observer based approach for precise estimation of battery SOC using super twisting algorithm. The proposed approach avoids overestimation of gains while ensuring finite-time convergence of the states. For choosing the associated adaptive gains, it does not demand any information on upper bounds of the uncertainty and its derivative, except for their existence. Unlike most of the sliding mode methods employed for SOC estimation, the proposed approach provides continuous control injection resulting in reduced chattering and eliminates the need for low pass filter that leads to improved accuracy and response time. Lyapunov stability theory is utilized to prove the robustness and the error convergence of the proposed observer. The presented algorithm is executed on a lithium-polymer battery and the obtained results demonstrate that it outperforms the well-established approaches in terms of accuracy, chattering, robustness, computational complexity, and convergence time. [ABSTRACT FROM AUTHOR]

This paper proposes a low-temperature coefficient (TC), noise, and offset bandgap reference (BGR) for the high precision applications. In order to reduce the offset voltage and noise introduced by the error amplifier, the offset and noise suppression technique is proposed. A five-piece linear compensation has been applied in the BGR to improve the TC performance. Moreover, an adaptive current loop is added to the bandgap reference to enhance the current driving capability. The proposed BGR is implemented in a $0.35~\mu \text{m}$ standard CMOS process occupying an active area of $0.22 \times 0.28$ mm2. The measured results show that the average TC is 3 ppm/°C −45 °C to 125 °C after trimming. The output reference voltage of 2.47 V can achieve $3.6~\mu \text{V}$ (rms) noise from 0.1 to 10 Hz. In the supply voltage range of 2.6 to 5 V, the proposed BGR can deliver $30~\mu \text{A}$ load current and its PSRR is about −83 dB @ 100Hz. [ABSTRACT FROM AUTHOR]

A high-voltage (HV) lithium-ion battery charger control chip with sharp mode transition and partial current control technique is proposed in this paper. The proposed sharp mode transition eliminates the transition region between constant current (CC) and constant voltage (CV) stages in traditional CC–CV chargers. This technique reduces the charging time and simplifies the compensator design. Furthermore, by adopting the HV partial current control technique, the charging current at the CC stage can be regulated only by sensing part of inductor current. The charger is designed and fabricated using Taiwan Semiconductor Manufacturing Company 0.25- $\mu \text{m}$ 1P3M bipolar-CMOS-DMOS HV process. With a 25-V input voltage, the output voltage (i.e., battery voltage) may range from 6 to 22 V and the maximum charging current is 2.5 A. The peak efficiency reaches 97%, occurring at 1-A charging current. [ABSTRACT FROM AUTHOR]

A pair of universal current mode control schemes for charging a Li-ion battery for mobile applications are discussed in this paper. The peak-current mode control schemes, based on a single control loop, is universal because it is designed with a single-stage buck charger for both a conventional wall adapter dc source as well as a solar photovoltaic (PV) module of comparable specifications. The charging schemes remove the need for an extra MPPT (maximum power point tracking) power converter stage. This control scheme is non-linear and incorporates all possible scenarios: mode of operation of a battery, current charging rate and power characteristic of input source. The algorithm uses need-based MPPT and ensures minimal battery discharge, and also uses minimum number of sense variables in the circuit. The methods differ in the way MPPT is implemented: perturb and observe (P&O) and fractional open circuit voltage. Simulation results demonstrating battery charge profile, validity of the algorithm under varying insolation conditions and platform workloads are presented, along with a discussion of the trade-offs of the two methods. Proof-of-concept hardware results are also provided. [ABSTRACT FROM AUTHOR]

This paper presents a fully integrated gas gauge system for mobile phone applications. It aims to consume a very small amount of power (less than 5%) compared to the whole system consumption during standby, maintaining a good level of accuracy in measuring battery energy in and out. It does not use any external bulky and expensive components beside the sense resistor and it has been manufactured in a CMOS 40 nm process and successfully validated in the lab. [ABSTRACT FROM PUBLISHER]

The self-powering, long-lasting, and functional features of embedded wireless microsensors appeal to an ever-expanding application space in monitoring, control, and diagnosis for military, commercial, industrial, space, and biomedical applications. Extended operational life, however, is difficult to achieve when power-intensive functions like telemetry draw whatever little energy is available from energy-storage microdevices like thin-film lithium-ion batteries and/or microscale fuel cells. Harvesting ambient energy overcomes this deficit by continually replenishing the energy reservoir and indefinitely extending system lifetime. In this paper, a prototyped circuit that precharges, detects, and synchronizes to a variable voltage-constrained capacitor verifies experimentally that harvesting energy electrostatically from vibrations is possible. Experimental results show that, on average (excluding gate-drive and control losses), the system harvests 9.7 nJ/cycle by investing 1.7 nj/cycle, yielding a net energy gain of approximately 8 nJ/cycle at an average of 1.6 μW (in typical applications) for every 200 pF variation. Projecting and including reasonable gate-drive and controller losses reduces the net energy gain to 6.9 nJ/cycle at 1.38 μW. [ABSTRACT FROM AUTHOR]

A built-in resistance compensator (BRC) technique is presented to speed up the charging time of a lithium-ion battery. A smooth control circuit (SCC) is proposed to ensure the stable transition from the constant-current (CC) to the constant-voltage (CV) stage. Due to the external parasitic resistance of the Li-ion battery-pack system, the charger circuit switches from the CC to the CV stage without fully charging the cell. The BRC technique dynamically estimates the external resistance to extend the CC stage. The experimental results show that the period of the CC stage can be extended to 40% of that of the original design. The charging time is effectively reduced. [ABSTRACT FROM AUTHOR]