In a battery management system (BMS), battery equalizer is used to achieve voltage consistency between series connected battery cells. Recently, serious inconsistency has been founded to exist in retired batteries, and traditional equalizers are slow or inefficient to handle the situation. The multicell-to-multicell (MC2MC) topology, which can directly transfer energy from consecutive strong cells to consecutive weak cells, is promising to solve the problem, but its performance is limited by the existing converter. Therefore, this paper proposes an enhanced MC2MC equalizer based on a novel bipolar-resonant LC converter (BRLCC), which supports flexible and efficient operation modes with stable balancing power, can greatly improve the balancing speed without much sacrificing the efficiency. Mathematical analysis and comparison with typical equalizers are provided to illustrate its high balancing speed and good efficiency. An experimental prototype for 8 cells is built, and the balancing powers under different operation modes are from 1.426 W to 12.559 W with balancing efficiencies from 84.84% to 91.68%.

Model predictive power control (MPPC) has been receiving plenty of concern owing to its fast dynamic response. However, the varying switching frequency makes the harmonics of output voltage vary over a wide scope, which adds difficulty in designing alternating current (AC) filter. Here, on the basis of the active and reactive power derivatives of each vector and the effect of switching states on neutral point (NP) voltage; we present a MPPC with dual vectors (MPPCDV) to control the three-level (3L) inverter. In this algorithm, a new switching sequence is provided to balance NP voltage of 3L inverter, and two cost functions are derived to reduce the number of cycle computation. According to the first cost functions, the sector containing optimal switching sequence (OSS) is obtained. The second cost function is assigned to achieve the multi-objective optimization. Simulations and experiments are built to test the effectiveness of MPPCDV. When the 3L inverter adopts the MPPCDV, the majority of the harmonic frequencies in output voltage are concentrated near the sample frequency, the steady-state performances are improved remarkably and the dynamic performance is as fast as the conventional MPPC.

Many battery equalizers have been proposed to achieve voltage consistency between series connected battery cells. Among them, the multicell-to-multicell (MC2MC) equalizers, which can directly transfer energy from consecutive more-charged cells to less-charged cells, can enable fast balancing and a high efficiency. However, due to the limitations of the equalizers, it is not possible to achieve fast equalization and reduce the size of the circuit at the same time. Therefore, a MC2MC equalizer based on a full-bridge bipolar-resonant LC Converter (FBBRLCC) is proposed in this paper, which not only implements MC2MC equalization, but also greatly reduces the circuit size by reducing the number of switches by nearly half. A mathematical model and simulation comparison with conventional equalizers are used to illustrate the high-speed equalization performance of the proposed equalizer and excellent balancing efficiency. An experimental prototype for eight cells is built to verify the performance of the proposed FBBRLCC equalizer and the balancing efficiencies in different operating modes are from 85.19% to 88.77% with the average power from 1.888 W to 14.227 W.

Even with the same voltage level, different types of battery packs have different requirements for the volume of the battery equalization circuit. However, most equalization circuits have the same problem: the volume of the equalization circuit is fixed once the voltage level of the battery pack is determined. In order to solve this problem, this paper proposes a novel lithium battery equalization circuit with any number of inductors (ECANI). It can select any number of inductors less than half the number of batteries, even when the voltage level of the battery pack is determined. Simulation and experiments are used to verify the performance of the equalization circuit. The current error and the average final voltage error in the experiment are 1.69% and 0.33% lower than those in the simulation, respectively. So the circuit can achieve equalization with good accuracy.

Model‐predictive direct‐power control (MPDPC) has attracted increasing attention from scholars because of its outstanding dynamic response and high‐power factor. However, its major shortcoming is the high‐computational cost, which limits its application in three‐level (3L) converters. By dividing the conventional MPDPC into two steps, a double‐step MPDPC (DMPDPC) algorithm is presented to address this problem. The first step of this algorithm is dedicated to searching a sector including an optimal switching state (OSS). In the second step, the OSS in a chosen sector is gained. Furthermore, its driver signals are changed as soon as the OSS is gained and their delay time is detected. Then, the corresponding delay compensation is also proposed to improve the steady‐state performance of the 3L‐converter. The validity of the proposed approach is demonstrated by the experimental platform with 4 kVA rated power. The experimental results show that the computing time in DMPDPC is 50.82% of that in conventional MPDPC. In addition, the proposed DMPDPC decreases the 3L converter's active and reactive powers ripples, reduces its current harmonic and strengthens its robustness against parameter variation.

Optimal-switching-sequence model-predictive-control (OSS-MPC) strategy, a popular kind of continuous-control-set MPC (CCS-MPC), has been used to address the variable frequency of finite-control-set MPC (FCS-MPC). Since the digital signal processor (DSP) does not have a dedicated divider, it requires a large amount of computation for the division operations in OSS searching. Here, a simplified OSS-MPC absorbing the merits of FCS-MPC is proposed to reduce the computational burden of conventional OSS-MPC. The proposed method uses a novel cost function whose candidates are the finite center vectors instead of switching sequences, which can avoid duty cycle computation and convert the moving horizon optimization of CCS-MPC into that of FCS-MPC. Besides, the derivatives of the active and reactive powers are divided into the constant terms and variable terms. The constant terms are extracted from the cost function. Experimental and simulation results show that the computational amount of the proposed algorithm is only 36.34% of that of the conventional OSS-MPC. Meanwhile, the simplified OSS-MPC still maintains the excellent dynamic and steady state performance of conventional OSS-MPC.