Constraint-Aware, Scalable, and Efficient Algorithms for Multi-Chip Power Module Layout Optimization

Moving towards an electrified world requires ultra high-density power converters. Electric vehicles, electrified aerospace, data centers, etc. are just a few fields among wide application areas of power electronic systems, where high-density power converters are essential. As a critical part of these power converters, power semiconductor modules and their layout optimization has been identified as a crucial step in achieving the maximum performance and density for wide bandgap technologies (i.e., GaN and SiC). New packaging technologies are also introduced to produce reliable and efficient multichip power module (MCPM) designs to push the current limits. The complexity of the emerging MCPM layouts is surpassing the capability of a manual, iterative design process to produce an optimum design with agile development requirements. An electronic design automation tool called PowerSynth has been introduced with ongoing research toward enhanced capabilities to speed up the optimized MCPM layout design process. This dissertation presents the PowerSynth progression timeline with the methodology updates and corresponding critical results compared to v1.1. The first released version (v1.1) of PowerSynth demonstrated the benefits of layout abstraction, and reduced-order modeling techniques to perform rapid optimization of the MCPM module compared to the traditional, manual, and iterative design approach. However, that version is limited by several key factors: layout representation technique, layout generation algorithms, iterative design-rule-checking (DRC), optimization algorithm candidates, etc. To address these limitations, and enhance PowerSynth’s capabilities, constraint-aware, scalable, and efficient algorithms have been developed and implemented. PowerSynth layout engine has evolved from v1.3 to v2.0 throughout the last five years to incorporate the algorithm updates and generate all 2D/2.5D/3D Manhattan layout solutions. These fundamental changes in the layout generation methodology have also called for updates in the performance modeling techniques and enabled exploring different optimization algorithms. The latest PowerSynth 2 architecture has been implemented to enable electro-thermo-mechanical and reliability optimization on 2D/2.5D/3D MCPM layouts, and set up a path toward cabinet-level optimization. PowerSynth v2.0 computer-aided design (CAD) flow has been hardware-validated through manufacturing and testing of an optimized novel 3D MCPM layout. The flow has shown significant speedup compared to the manual design flow with a comparable optimization result

Sensors Fault Diagnosis Trends and Applications

Fault diagnosis has always been a concern for industry. In general, diagnosis in complex systems requires the acquisition of information from sensors and the processing and extracting of required features for the classification or identification of faults. Therefore, fault diagnosis of sensors is clearly important as faulty information from a sensor may lead to misleading conclusions about the whole system. As engineering systems grow in size and complexity, it becomes more and more important to diagnose faulty behavior before it can lead to total failure. In the light of above issues, this book is dedicated to trends and applications in modern-sensor fault diagnosis

Reduced-order electro-thermal models for computationally efficient thermal analysis of power electronics modules

Silicon and Silicon Carbide-based power module are common in power electronic systems used in a wide range of applications, including renewable energy, industrial drives and transportation. Reliability of power electronics converters is very important in many applications. It is well known that reliability and ultimately the lifetime of power modules is affected by the running temperature during power cycles. Although accurate thermal models of power electronics assemblies are widely available, based e.g. on computational fluid dynamics (CFD) solvers, their computational complexity hinders the application in real-time temperature monitoring applications. In the thesis, geometry-based numerical thermal models and compact thermal models will be developed to address the fast thermal simulation in the electronic design process and real-time temperature monitoring, respectively. Accurate geometry-based mathematical models for dynamic thermal analyses can be established with the help of finite difference methods (FDM). However, the computational complexity result from the fine mesh and large dimension of ordinary differential equations (ODE) system matrix makes a drawback on the analysis in parametric studies. In this thesis, a novel multi-parameter order reduction technique is proposed, which can significantly improve the simulation efficiency without having a significant impact on the prediction accuracy. Based on the block Arnoldi method, this method is illustrated by referring to the multi-chip power module connected with air-force cooling system including plate-fin heatsink. In real-time temperature monitoring, more compact tools might be preferable, especially if operating and boundary conditions such as losses and cooling are now known accurately, as it’s often the case in practical applications. Compared with geometry-based model which is more suitable in the design of power modules, lumped parameter thermal compact model is simpler and can be applied in real-time temperature prediction during the power cycles of power modules. This thesis proposes a reduced order state space observer to minimize the error caused by air temperature and air flow rate. Additionally, a novel feedback mechanism for disturbance estimation is introduced to compensate the effect result from the error of input power loss, air flow and changes of other nonlinearities

In-Field Observations of Heavy Mining Vehicle Wheels and Analyses of Proposed Solutions to Enhance Safety

This research strives to enhance the safety of multi-piece wheel assemblies as injuries and fatalities are associated with their failure, yet information on this topic is limited. Experiments were performed to determine mechanical performance and planar deformation characteristics of several tires to aid in numerical model development. For a 29.5-29 tire, observations included determining vertical versus lateral deflection relationships (0.310 mm/mm), and vertical (2.59 kN/mm) and lateral (6.29 kN/mm) stiffness. A database capable of tracking wheel maintenance trends based on historical data was developed, allowing maintenance schedules to be estimated. A safety shield system was proposed. Effectiveness of the design was examined through numerical simulation of the ISO 7141 impact test, a tire blowout, and a rotational side impact. Depending on the test condition, observations comparing shield-equipped versus standard wheels show reductions in von Mises stress between 15% and 55% and reductions in effective plastic strains between 20.3% and 92%

Modelling and simulation of paradigms for printed circuit board assembly to support the UK's competency in high reliability electronics

The fundamental requirement of the research reported within this thesis is the provision of physical models to enable model based simulation of mainstream printed circuit assembly (PCA) process discrete events for use within to-be-developed (or under development) software tools which codify cause & effects knowledge for use in product and process design optimisation. To support a national competitive advantage in high reliability electronics UK based producers of aircraft electronic subsystems require advanced simulation tools which offer model based guidance. In turn, maximization of manufacturability and minimization of uncontrolled rework must therefore enhance inservice sustainability for ‘power-by-the-hour’ commercial aircraft operation business models. [Continues.

Advances in Automated Driving Systems

Electrification, automation of vehicle control, digitalization and new mobility are the mega-trends in automotive engineering, and they are strongly connected. While many demonstrations for highly automated vehicles have been made worldwide, many challenges remain in bringing automated vehicles to the market for private and commercial use. The main challenges are as follows: reliable machine perception; accepted standards for vehicle-type approval and homologation; verification and validation of the functional safety, especially at SAE level 3+ systems; legal and ethical implications; acceptance of vehicle automation by occupants and society; interaction between automated and human-controlled vehicles in mixed traffic; human–machine interaction and usability; manipulation, misuse and cyber-security; the system costs of hard- and software and development efforts. This Special Issue was prepared in the years 2021 and 2022 and includes 15 papers with original research related to recent advances in the aforementioned challenges. The topics of this Special Issue cover: Machine perception for SAE L3+ driving automation; Trajectory planning and decision-making in complex traffic situations; X-by-Wire system components; Verification and validation of SAE L3+ systems; Misuse, manipulation and cybersecurity; Human–machine interactions, driver monitoring and driver-intention recognition; Road infrastructure measures for the introduction of SAE L3+ systems; Solutions for interactions between human- and machine-controlled vehicles in mixed traffic

Advanced Diagnostic Techniques Applied to Polymer Electrolyte Fuel Cells

Polymer electrolyte fuel cells (PEFCs) are among the most promising energy conversion technologies for a broad range of applications, offering zero-emission electricity generation by converting hydrogen directly into electrical energy at high efficiencies. Tremendous advancements have been made in terms of performance and durability but technological challenges still exist which hinder their widespread adoption; these challenges range from material durability to system design and operating strategies. Developing this technology requires a comprehensive understanding of its fundamental operation, coupled with effective diagnostic techniques. Performance, temperature and hydration in a PEFC is a complex relationship governed by cause-and-effect, where a change in one factor alters the other. These problems are exacerbated during scale-up, advancing from small lab-scale single cells to large commercial automotive stacks, where operational heterogeneities encourage large current and temperature variations, resulting in varied local degradation rates and inefficient PEFC performance. This study characterises these parameters in-operando by adopting diagnostic techniques such as current, temperature and pressure mapping, coupled with electrochemical techniques, to garner a broader understanding of the formation of these heterogeneities. The development of new diagnostic techniques for both research and industry is also crucial for the commercialisation of PEFCs, as stack-level diagnostic resources are limited. These are required to be straightforward in application and interpretation, cost-effective and with short testing times. Novel diagnostic techniques are presented in this study which aim to bridge this gap in the diagnostic sector. Lock-in thermography is used to image sub-surface water content during cell operation using a thermal imaging camera, producing water distribution images at various penetration depths. A complementary transfer function technique is also developed, termed heat-stimulus thermo-electric impedance spectroscopy (HS-TEIS), which considers the complex relationship between imposed temperature change and electrical response as a function of frequency