A gate driving for power devices is a key technology to further improve switching characteristics. With the help of digital gate driver IC, the switching behavior of power devices can be enhanced even under high-speed switching. In this paper, an evaluation platform for determining the optimal switching pattern of an active gate drive control is proposed for an inverter circuit. A high speed optimization system is built up to search for an advantageous switching pattern that reduces total switching loss of two power devices in an inverter circuit and constrains surge voltage simultaneously. The proposed online optimization demonstrates its feasibility for the full-bridge inverter circuit, which is rated at 500 V with digital active gate drive control. Experimental results show that the proposed optimization system is able to obtain optimal switching pattern from $64^{60}$ possible combinations of switching patterns within 15 min, which is 6 times faster than the previous study. Optimizations can also conducted under different load current conditions. Eventually, the obtained optimal pattern yields up to 42% reduction in the total switching loss when it constrains surge voltage to minimum compared with the conventional driving pattern.

Lithium-ion (Li-ion) batteries play a substantial role in portable consumer electronics, electric vehicles and large power energy storage systems. For Li-ion batteries, developing an optimal charging algorithm that simultaneously takes rises in charging time and charging temperature into account is essential. In this paper, a model predictive control-based charging algorithm is proposed. This study uses the Thevenin equivalent circuit battery and transforms it into the state-space equation to develop the model predictive controller. The usage of such models in the battery optimal control context has an edge due to its low computational cost, enabling the realization of the proposed technique using a low-cost Digital Signal Processor (DSP). Compared with the widely employed constant current-constant voltage charging method, the proposed charging technique can improve the charging time and the average temperature by 3.25% and 0.76%, respectively.

Model-free predictive current control (MFPCC) is a promising substitute for model predictive current control (MPCC). However, the performance of the MFPCC, to a large extent, hinges on the update frequency of its lookup table. Conventionally, the update is only performed when two successive switching states applied by the controller are identical, causing a stagnation problem to the current difference of those switching states that are not applied. To address the stagnation problem, this paper proposes a novel mechanism called synchronized current difference update for model-free predictive current control (SCDU-MFPCC). The presented scheme uses the model of permanent-magnet synchronous motor (PMSM) to construct equivalent differential stator currents corresponding to seven basic voltage vectors. To that end, current slope will be defined from the current difference of two successively applied voltage vectors. An updating factor associated with the current slope is then introduced into the prediction scheme to correct the enforced response of all switching states. This scheme is applied on every current measurement to update the stored information regardless of the successive switching states applied are distinct or not. Finally, experiments are conducted to assess the performance of the new approach using a TMS320F28379D microcontroller. Experimental results demonstrate that the proposed method substantially reduces the stagnation effect under steady-state and dynamic operations.

Digital active gate driving has been shown to effectively manage the switching performance for power devices with the adjustable driving waveforms. However, most of the studies are based on a dedicated test circuit rather than a practical inverter with the sinusoidal output current. In fact, it is the dependence on the load current that makes the design of the gate driving profiles a critical issue. To investigate the digital active gate driver in an inverter application, this article has applied optimal patterns adapting to time-varying output load current. Prior to the search of optimal patterns, the proper design of time slot is discussed with three different time resolutions. With the proper resolution determined for patterns, multiple optimizations are carried out for different current conditions. In this way, the search for optimal patterns can be completed in an efficient time. Next, a lookup table of optimal switching pattern in correspondence with each certain load current condition was built in advance. According to the output load current, the optimal pattern is selected based on the lookup table. Compared to conventional constant driving waveform, the power loss has been reduced by 7% with full optimal lookup table applied.

This article proposes a new optimization method and its platform for automatically adjusting the control parameters of a digital active gate driver while operating a pulse-width modulation (PWM) inverter. The proposed optimization method applies the searching parameters for some sectors in an ac current cycle and fixed parameters for the other sectors. This enables us to find the optimal operating points of power devices so as to reduce the surge voltage and switching loss with the consideration of their dependency on the load current. Additionally, the proposed optimization method also can find the operating points while the inverter performs a continuous switching operation. For this reason, the proposed optimization method can be applied to a continuous running test of PWM inverters, for example, in a manufacturing process. The validity of the proposed method and platform was evaluated by using a 10-kW three-phase PWM inverter with digital gate drives. The experimental results confirmed that the proposed optimization method makes it possible to find the optimal operating points for reducing the surge voltage and/or the power loss.

A model-free predictive current control for synchronous reluctance motor drives based on triple-voltage-vector with optimized duty ratio modulation is presented in this paper. The proposed scheme introduces an effective and low complexity strategy of selecting candidate voltage vectors to largely reduce computational loadings. First, the basic voltage vectors are organized to apportion six regions, representing six composite switching modes. Each region comprises two active voltage vectors and a zero voltage vector modulated by distinct duty ratios. The scheme starts from the selection of an initial basic voltage vector corresponding to a predefined cost function. The second candidate voltage vector then follows, which is chosen from the region adjacent to the initial one. The third vector is a default zero voltage vector. As a result, voltage vectors outside the selected regions are excluded from the process. Moreover, the adjustable feature makes the optimization of duty ratios adaptive. Finally, the proposed method is experimentally put to tests under various operating conditions utilizing the synchronous reluctance motor drives. Experimental results are presented to demonstrate the effectiveness of the proposal.