The conventional model predictive control (MPC) suffers from high common-mode voltage (CMV) magnitude and large current ripples. In this paper, the reduced CMV MPC strategy with double vector (RCMV-MPCDV) is proposed for three-level inverters, which adopts double vector to reduce the CMV and current ripple simultaneously in per-sampling period. Firstly, based on geometric relationship of median, a novel cost function that evaluate median line distance is proposed to reduce the computational complexity, rather than evaluating the closest distance. Secondly, in order to reduce the computational burden, the double vector preselection (DVP) algorithm is presented with fewer evaluation times. Thirdly, the candidate vectors are reclassified and regrouped from partial basic vectors, which restricts CMV magnitude within one-sixth of DC-link voltage. In addition, to select more satisfactory double vectors for RCMV-MPCDV scheme, two improved methods are proposed to compensate the losing candidate vectors. The simulation and experimental results with steady-state performance and dynamic response validate the effectiveness of the proposed method.

The improved LCL (ILCL) filter is used in transformerless three-level photovoltaic inverter system for leakage current suppression. However, the common-mode (CM) resonance circulating current (CMRCC) is generated, which causes inverter-side current oscillation, leakage current increment and system instability. To overcome these issues, an improved CM circulating current (CMCC) model with detailed analyses of CMRCC is proposed. Based on above theories, the CMRCC is influenced by filter parameters, zero-sequence duty ratio and number of switching transition. To suppress CMRCC, a hybrid control strategy composed of PI and feed-forward control is presented. It is realized by real-time adjusting zero-sequence duty ratio in space vector modulation (SVM) technique. Compared with the conventional damping resistor techniques, the CMRCC and leakage current are effectively suppressed with the proposed method. Thus, the performance of inverter-side currents and leakage current suppression are greatly improved. Besides, the capacitor-voltage-feedforward (CVF) control is adopted to eliminate resonance peak in differential-mode (DM) circuit. Simulation and experimental results are given to demonstrate the effectiveness of theoretical analyses and the proposed method.

The conventional three-level inverter only has voltage buck capability. The quasi-Z-source three-level T-type inverter (QZS 3LT $^2$ I) has been proposed to realize voltage buck-boost operation. This paper further proposes a novel modulation scheme for the QZS 3LT $^2$ I to realize voltage boosting, reduce the common-mode voltage (CMV) and control the neutral-point voltage balance simultaneously. The proposed scheme adopts large vector, medium vector, small vector with low CMV magnitude, zero vector, and shoot-through vector to generate the output voltage. According to sector number and neutral-point voltage difference, P-type or N-type small vector with low CMV magnitude is properly selected to balance the neutral-point voltage. Shoot-through states are inserted within zero vector to boost the dc input voltage without affecting the ac output voltage. Dwell times of basic vectors are calculated through the revised volt-second balance equation. Furthermore, a coordinate control strategy between neutral-point voltage balance and voltage boosting is proposed. Doing so, the CMV magnitude can be restricted within one-sixth of dc-link voltage, and neutral-point voltage imbalance can be effectively mitigated. The effectiveness of the proposed scheme are verified by simulations and experiments.

Recently, a few fault-tolerant control strategies have been proposed for T-type three-level inverters to improve the reliability of the inverter system. However, the neutral-point (NP) voltage oscillations suppression is never considered in the previous fault-tolerant control strategies. In order to suppress the NP voltage oscillations when open-circuit fault occurs to NP switches, this paper proposes two novel fault-tolerant control strategies named as improved two-level switching tolerant control (I2LS-TC) and hybrid switching tolerant control (HS-TC). Both methods are implemented by adding an optimal time-offset to the three-phase turn-on times. The corresponding time-offset value of each method is simply calculated considering the phase current and dwell time of [O] state. Moreover, a NP voltage balancing algorithm to eliminate the dc deviation and a dc bias to further reduce the NP voltage oscillations are used in the HS-TC. The performance and comparison of the tolerant controls with respect to the NP voltage oscillations, current total harmonic distortion (THD) and dynamic response are illustrated and analyzed through the simulation and experimental results.

Accurately estimating the capacity of lithium-ion batteries in electric vehicles (EVs) is critical for making correct management decisions. However, the randomness of the charging voltage range of EVs can lead to missing observations or reduced accuracy of capacity estimation methods. This article proposes an adaptive battery capacity estimation method suitable for arbitrary charging voltage range based on incremental capacity (IC) analysis and data-driven techniques. All charging conditions of EVs are divided into three categories according to the charging voltage range. Three data-driven estimation submethods with sequential application priority are designed for the three charging conditions separately, including back-propagation neural network with IC peak coordinates as input, ensemble learning with local high IC curve as input, and linear regression with ampere-hour coordinate transformation. The method is based on a priori knowledge to select a suitable estimation submethod under different charging conditions, so as to improve the adaptability. Experimental data is collected from eight commercial lithium-ion battery modules for model establishment and verification. Over 250 000 experimental samples at different states of health and random charging ranges show that the method can accurately estimate battery capacity under arbitrary charging conditions, with a maximum error of 2%.

Paralleled three-level T-type inverters face the unavoidable pitfall of the zero-sequence circulating current (ZSCC). Although the conventional model predictive control (MPC) could eliminate the ZSCC, the control error occurs inevitably since only one vector is adopted in each sampling period, which decreases the current control performance. Thus, simultaneous ZSCC elimination and accurate current tracking become imperative to the inverter using MPC. This article proposes a multivector MPC to eliminate the ZSCC and reduce the current distortion without the weighting factor. As the common-mode voltage (CMV) and neutral point (NP) voltage are the main factors that induce the ZSCC, the virtual vector with zero-average CMV is constructed to eliminate the ZSCC. Meanwhile, the small vector is introduced to improve the NP voltage control capability. In addition, to enhance the current accuracy and reduce the ZSCC ripple, three optimal vectors are adopted to synthesize desired voltage. Moreover, the multivector preselection algorithm is proposed to reduce the computational complexity of implementation process. Finally, the effectiveness of the proposed method is verified with comprehensive simulation and experimental results.