The contest consists of 200 seconds videos which are evaluated by three judges based on key aspects such as problem definition, design methodology, outcomes, and quality of the presentation.

Competing with people from all over the world, Emanuel, from #MartinOrdonezLab, secured the prize with an outstanding presentation on Advanced Control Functionalities for Photovoltaic and Energy Storage Converters. His talk will be presented at the end of September at The Eleventh Annual Energy Conversion Congress and Exposition, at Baltimore, Maryland, USA. 

Congratulations Emanuel for this great achievement!

Last Monday, on the 29th of July 2019, Matthieu Amyotte successfully graduated from his MASc program in our lab. Matt’s great achievements include but are not limited to the following:

• 3 IEEE International Conference papers (one as first author) and 1 IEEE Journal publication (submitted).

• Major contributions to our UBC Sustaingineering Team.

• Key involvement in the research collaboration projects with our industry partner, Alpha Technologies Ltd., on WBG switch losses.

• A number of great contributions to our lab’s operations and logistics

Right after graduation Matt successfully transitioned to the industry by taking a position at Corvus Energy, Richmond, BC.

We congratulate Matt for achieving this significant milestone in his career and wish him success in all future endeavours!

Abstract for Matt’s MASc thesis
Title: “Improved Power Loss Estimation for Device- to System-Level Analysis”
Abstract: Power converters are found nearly everywhere electric power is used and are ubiquitous in renewable energy generation and electric vehicles. Power converters transform electricity between alternating current (AC) and direct current (DC) electricity and change the voltage level (AC or DC). Modern power converters have very high efficiency, often reaching peak efficiency > 95%. However, the losses in these systems are still significant and must be considered for thermal and financial purposes. For example, a 1% efficiency improvement from 98 to 99% corresponds to a 50% reduction in losses. This would allow for a significant reduction, if not the complete elimination, of the thermal management system. To enable maximum loss reduction, a thorough understanding of the losses in power converters is necessary. In particular, accurate prediction of the losses at the design stage allows designers to create better power converters and energy systems with lower losses. Gallium Nitride (GaN) power switches are an emerging technology due to their high efficiency operation and smaller size compared to traditional Silicon (Si) devices. To date, traditional topologies, such as boost and resonant converters, have been implemented with Gallium Nitride (GaN) devices, and simplistic power loss models have been employed for loss predication and thermal management design. However, these simplistic models do not provide accurate loss prediction, resulting in over-design of the thermal management systems. Meanwhile, high accuracy power loss analysis tools for GaN devices are missing in the literature. With very small footprints and thermal capacity, accurate power loss prediction for GaN is mandatory. This work proposes a comprehensive method to predict conduction and switching losses in GaN devices. Through the use of thermal measurement, the inaccuracy of traditional electrical measurements for power losses is eliminated and a higher accuracy model is achieved. The proposed model is verified experimentally against common traditional approaches. The proposed model provides a nearly four-fold reduction in loss prediction error across a variety of operating conditions. Ultimately, the model provides confidence in loss prediction, allowing power converter designers to effectively design thermal management systems for maximum power density and efficiency. Having established accurate converter-level loss prediction, a higher level of abstraction is then considered. The rapid expansion of distributed energy resources has led to increasingly complex systems with numerous power converters. Given the pervasiveness of power converters in both large grids and microgrids, accurate converter loss prediction is essential for system-level financial and reliability evaluation. Existing system-level analysis focuses on distribution losses and oversimplifies converter losses by assuming fixed efficiency. In reality, converter losses are highly variable under different operating conditions. However, the multi-domain simulation tools employed for GaN loss prediction at the converter level are too slow to be applied to system-level analysis. In this work, the Rapid Loss Estimation equation (RLEE) is proposed to provide computationally simple loss prediction under all operating conditions. First, the real operating conditions are determined for the intended application. Then, accurate loss information is extracted from detailed converter behavior in multi-domain simulations at select operating conditions. Finally, the RLEE is obtained: a parametric equation which is fast enough for system-level simulation while capturing the converter’s complexity at different operating conditions. Three different converters are considered: one for solar generation, one for electric vehicle charging stations and one for battery storage. These converters are simulated in a DC microgrid to highlight the benefits of the proposed loss estimation tool. Ultimately, the tools developed in this work provide improved loss estimation in power converters from the component level through to the system level. The proposed techniques, while explained through specific examples, are widely applicable and can be readily implemented to other devices, topologies and systems. Improved loss estimation is valuable at all levels of abstraction, from designing thermal management systems for individual devices in a converter to optimizing the financial outcomes of a complex grid with multiple power converters.

Last Friday, on the 5th of July 2019, Mehdi Mohammadi successfully graduated from his PhD program in our lab. Mehdi’s great achievements include but are not limited to the following:

• Over 10 IEEE Publications.

• A patent.

• President of the UBC’s ECE Graduate Student Association (@ECEGSA).

Right after graduation Mehdi successfully transitioned to the industry by taking a position at Fortinet Technologies (Canada).

We congratulate Mehdi for achieving this significant milestone in his career and wish him success in all future endeavours!

Abstract for Mehdi’s PhD thesis
Title: “Three-Layer Control Strategy for LLC Converters: Large Transient, Small-Signal, and Steady-State Operation”
Abstract: Resonant converters, particularly LLC converters, feature low switching losses and electromagnetic interference (EMI), and high power density and efficiency. As a result, they have been widely used in DC/DC applications. Although LLC converters naturally provide soft switching conditions and therefore, produce relatively less switching losses, conduction losses in their rectifier have remained a barrier to achieving higher efficiencies. Moreover, the analysis of LLC converters is complicated since they process the electrical energy through a high-frequency resonant tank that causes excessive nonlinearity. The issue of this complexity becomes even worse since, in reality, the resonant frequency of such converters deviates due to variations in the temperature, operating frequency, load, and manufacturing tolerances. This complexity has caused:

• limited research on large-signal modeling and control of LLC converters to be performed (this leads to uncertain large-signal transient behavior and sluggish dynamic/recovery response).

• limited insight into small-signal modeling of LLC converters (this often leads to low accuracy).

• unregulated LLC converters not to operate in their optimum operating point (this leads to degraded efficiency and gain).

• conduction losses in the LLC rectifier to remain the main challenge to achieve higher efficiency

To address the above concerns, in this dissertation, a three-layer control strategy is introduced. Based on the need, all the three layers or just one of them can be used when implementing the LLC converter. The three-layer control strategy produces accurate and fast dynamics during start-up, sudden load or reference changes with near zero voltage overshoot in the start-up, obtains a near zero steady-state error by employing a second-order average small-signal model valid below, at, and above resonance, improves efficiency by a new synchronous rectification technique, and also tracks the series resonant frequency in unregulated DC/DC applications.