• Energy Research

Pulsewidth-modulated (PWM) inverters are used more and more to operate electrical machines and to interface renewable energy systems with the utility grid. However, there are abundant high-frequency harmonics in the output voltage of a PWM inverter, which increase the iron losses and result in derating of the machine or transformer connected to them. Predicting the iron losses caused by the PWM supply is critical for the design of electrical machines and transformers operated by PWM inverters. These losses are primarily attributed to eddy-current loss caused by the PWM supply. In this paper, after analyzing the harmonic components of PWM voltage, we derive the effects of different parameters of PWM switching on the eddy-current loss. We compare the iron losses modeled with the proposed analytical methods on a three-phase transformer, a dc motor, and an induction motor with the results of time-stepping finite-element analysis and experiments. We provide detailed equations for the prediction of iron losses. These equations can be directly applied in the design and control of PWM converters and electric motors to improve energy efficiency in electrical machines and transformers operated from PWM converters.

Abstract The correlation between state of charge (SoC) and open-circuit voltage (OCV) is a crucial characteristic parameter in many aspects of the battery management system (BMS). However, it is a challenging task to obtain the accurate SoC-OCV correlation with a high test efficiency. In this paper, an improved OCV characterization test is proposed to actively reduce the polarization voltage. Based on the third-order equivalent circuit model (ECM), two sets of current pulses are applied to accelerate the convergence of the battery terminal voltage, thus the test time is effectively shortened compared to the conventional incremental OCV characterization test. Furthermore, the parametric sensitivity of the imposed current excitation to battery model parameters is analyzed. Subsequently, the parametric determination method for the imposed current excitation is provided. Experiments are conducted on a lithium-ion polymer battery to prove the feasibility of the proposed test procedure. Comparison with the conventional OCV characterization test further demonstrated the superiority of the proposed test procedure.

The conventional state-of-charge (SoC) estimation methods based on the equivalent circuit model (ECM) integrate all state variables into one augmented state vector. However, the correlations between RC voltages and SoC degrade the stability and accuracy of the estimates. To address this problem, this paper presents an adaptive SoC estimation method based on the split battery model, which divides the conventional augmented battery model into two submodels: the RC voltage submodel and the SoC submodel. Hence, the cross interference between RC voltages and SoC is reduced, which effectively reduces the oscillation in the estimation and improves the estimation accuracy. In addition, the adaptive algorithm is applied on the SoC submodel to improve the system robustness to noise disturbances. A case of a second-order ECM is analyzed and two types of Lithium-ion batteries are employed to verify the universality of the proposed method. Experimental results show that the undesired oscillation is eliminated during the convergence stage and the maximum SoC error is within 1% over a wide SoC range.

This paper studies the characteristics of battery packs with parallel-connected lithium-ion battery (LiB) cells. To investigate the influence of the cell inconsistency problem in parallel-connected cells, a group of different degraded LiB cells were selected to build various battery packs and test them using a battery test bench. The physical model was developed to simulate the operation of the parallel-connected packs. The experimental results and simulation indicate that, with different degraded cells in parallel, there could be capacity loss and large difference in discharge current, which may cause further accelerated degradation and a more serious inconsistency problem.

This paper proposes a single-phase, transformer-less, seven-level inverter that utilizes eight switches, three capacitors, and two diodes to produce seven voltage levels with triple boosting ability. The availability of the common-ground point eliminates the leakage current in PV applications. The proposed Transformer-Less Triple-Boosting Seven-Level Inverter (TLTB7LI) has the ability to feed different types of loads from non-unity to unity power factors. The voltage balancing of capacitors takes place naturally without the need for auxiliary circuits and complicated control strategies. This paper investigates the appropriateness of the proposed TLTB7LI for grid-connected application. The Peak Current Controller (PCC) is employed to generate the switching pulses and regulate the active/reactive power transfer between the converter and the output, which guarantees the high quality of injected current to the output. Moreover, the operational principles, its control technique, as well as the design procedure of the key components of the proposed inverter have been presented. The superiority of the proposed inverter over existing counterparts has been verified through comparative analysis. The simulation and experimental analysis validated the proper operation of the proposed TLTB7LI.

Four model-based State of Charge (SOC) estimation methods for lithium-ion (Li-ion) batteries are studied and evaluated in this paper. Different from existing literatures, this work evaluates different aspects of the SOC estimation, such as the estimation error distribution, the estimation rise time, the estimation time consumption, etc. The equivalent model of the battery is introduced and the state function of the model is deduced. The four model-based SOC estimation methods are analyzed first. Simulations and experiments are then established to evaluate the four methods. The urban dynamometer driving schedule (UDDS) current profiles are applied to simulate the drive situations of an electrified vehicle, and a genetic algorithm is utilized to identify the model parameters to find the optimal parameters of the model of the Li-ion battery. The simulations with and without disturbance are carried out and the results are analyzed. A battery test workbench is established and a Li-ion battery is applied to test the hardware in a loop experiment. Experimental results are plotted and analyzed according to the four aspects to evaluate the four model-based SOC estimation methods.

Abstract Battery state-of-health (SoH) estimation is a critical function in a well-designed battery management system (BMS). In this paper, the battery SoH is detected based on the dynamic characteristic of the charging current during the constant-voltage (CV) period. Firstly, according to the preliminary analysis of the battery test data, the time constant of CV charging current is proved to be a robust characteristic parameter related to the battery aging. Secondly, the detailed expression of the current time constant is derived based on the first order equivalent circuit model (ECM). Thirdly, the quantitative correlation between the normalized battery capacity and the current time constant is established to indicate the battery SoH. Specifically, for the uncompleted CV charging process, the logarithmic function-based current time constant prediction model and the reference correlation curve are established to identify the battery capacity fading. At last, experimental results showed that regardless of the adopted data size, the correlation identified from one battery can be used to indicate the SoH of other three batteries within 2.5% error bound except a few outliers.

Gold-nanoparticle-based hyperthermia has attracted considerable attention in the recent ten years in cancer treatment. In hyperthermia-based cancer treatment, in order to produce efficient thermal therapy yet without excessive heat damage to human body, besides the steady-state thermal condition, the transient thermal response is of vital importance. As part of theoretical research associated with nanoparticle-mediated hyperthermia therapy for cancer treatment, the transient heat transfer process of laser interacting with gold nanoparticle in tissue-like medium is investigated. Within the framework of dual-phase-lag (DPL) model, this paper focuses on the microscopic heat transfer performance of a gold nanoparticle in a surrounding medium. A semianalytical solution of 1-D nonhomogenous DPL equation in spherical coordinates is presented for a heat transfer process with a constant laser heat source and a short-pulsed laser heating source. Results show that the transient temperature calculated by DPL model greatly exceeds that predicted by the classical diffusion model, with either a constant source or a pulsed source. This phenomenon is mainly attributed by the phase lag of heat flux in the surrounding tissue.

With the development of power electronic techniques, pulse-width modulated (PWM) inverters are widely used to control electrical machines, to feed transformers and to interface renewable energy systems. There are abundant high frequency harmonics in the output voltage of a PWM inverter, which increase the iron loss and result in a de-rating of the machine or transformer. Predicting the iron losses caused by the PWM voltage is very important for the design of electrical machines and transformers fed by PWM inverters. Eddy current loss is the main part of the iron loss caused by PWM. In this paper, after analyzing the harmonic components of PWM voltage, the effects of different parameters of PWM on the eddy current loss are derived. The relationship of eddy current losses with switching frequency and amplitude modulation ratio is considered. The iron losses modeled with the proposed analytical methods of a single phase transformer are compared with results of time-stepping finite element analysis to gain confidence. The relationship of duty cycle and eddy current loss of PWM supplied DC motors is also studied in this paper.