Finite Element Modeling and Analysis of High Power, Low-loss Flux-Pipe Resonant Coils for Static Bidirectional Wireless Power Transfer

This paper presents the optimal modeling and finite element analysis of strong-coupled, high-power and low-loss flux-pipe resonant coils for bidirectional wireless power transfer (WPT), applicable to electric vehicles (EVs) using series-series compensation topology. The initial design involves the modeling of strong-coupled flux-pipe coils with a fixed number of wire-turns. The ohmic and core loss reduction for the optimized coil model was implemented by creating two separate coils that are electrically parallel but magnetically coupled in order to achieve maximum flux linkage between the secondary and primary coils. Reduction in the magnitude of eddy current losses was realized by design modification of the ferrite core geometry and optimized selection of shielding material. The ferrite core geometry was modified to create a C-shape that enabled the boosting and linkage of useful magnetic flux. In addition, an alternative copper shielding methodology was selected with the advantage of having fewer eddy current power losses per unit mass when compared with aluminum of the same physical dimension. From the simulation results obtained, the proposed flux-pipe model offers higher coil-to-coil efficiency and a significant increase in power level when compared with equivalent circular, rectangular and traditional flux-pipe models over a range of load resistance. The proposed model design is capable of transferring over 11 kW of power across an airgap of 200 mm with a coil-to-coil efficiency of over 99% at a load resistance of 60 Ω

Impact of Coil Turns on Losses, Output power and Efficiency Performance of Flux-Pipe Resonant Coils

This paper presents a finite element analysis of five different sizes of flux-pipe resonant coil design with a different number of coils turns but having the identical length of litz copper wire and aluminum shield. The analysis was undertaken to establish the impact of the number of coil turns on the losses, magnetic flux distribution, power output, and power transfer efficiency of flux-pipe resonant coils. From the results presented, it was noted at a constant frequency, an increase in the excitation current causes a significant increase in the ohmic, core, and eddy current losses for each of the coil model designs. Similarly, at constant excitation current, it was observed that the eddy current losses increase significantly with an increase in resonant frequency. In contrast, the ohmic and core losses are relatively constant over the range of resonant frequencies used in the analysis. It was also noted that term k√Qps (where k is the coupling coefficient and Q ps is the product of the quality factor of the primary and secondary coils) has a significant influence on the input power, output power and coil-to-coil efficiency of a particular flux-pipe resonant coil design. Increasing the value of k√Qps increases the value of output power, input power, and coil-to-coil efficiency. Similarly, the lower the coupling coefficient, the higher the required optimum resonant frequency for optimum coil-to-coil efficiency and output power

Loss Performance Evaluation of Ferrite-Cored Wireless Power System with Conductive and Magnetic Shields

This paper presents a loss evaluation of ferrite-cored wireless power transfer (WPT) systems using conductive and magnetic shield materials. The modelling and analyses of the coil systems were implemented using the finite element method. Three coil systems were modelled-circular coils, rectangular coils and flux-pipe coil system using magnetic shields (Mumetal and electrical steel) and conductive shields (aluminum and copper). From the results presented in the analyses, it was noted that ohmic losses and core losses in the WPT system are independent of the type of conductive shield used. Similarly, it was noted that the self-inductance, coupling coefficient and losses in the system is affected by the type of magnetic shield used. For the flux-pipe resonant coil system, high power losses were recorded when a magnetic shield was used as the shielding topology while low power losses were recorded in the circular coil and rectangular coil resonant systems when the magnetic shield was used as the shielding material. For optimal WPT system requiring low eddy current losses, it was established that copper shield is the appropriate choice for flux-pipe resonant coils while electrical steel is the suitable shield material for the circular resonant coil and rectangular resonant coil systems

Optimal Finite Element Modelling and 3-D Parametric Analysis of Strong Coupled Resonant Coils for Bidirectional Wireless Power Transfer

Resonant coils can be utilised for the wireless transfer of power between a supply grid and an electric vehicle. In order to achieve an affordable and optimal resonant coil design, the coupling factor becomes a significant parameter. The coupling factor (k) indicates the percentage of the total magnetic flux responsible for the transfer of electrical power from the transmitter to the receiver. A higher value of k will increase the magnitude of real power transferred between coils as well as reduce in the proportion of reactive power circulating in the system. For optimal and efficient bidirectional Wireless Power Transfer (WPT) operation, the primary and secondary coils must be designed to achieve a high Quality factor (Q) and high coupling factor. Using the same length of copper wire and volume of ferrite core, three simple resonant coils using finite element modelling (FEM) designs are proposed: circular, rectangular and double-sided winding coils. The physical length (D) of the coils is restricted to be no more than 600 mm due to the physical diameter of most electric cars as well as regulations governing electromagnetic radiations. Magnetostatic performance analyses of the coil designs to confirm mutual inductances, coupling factors, the maximum magnetic flux density (B) distributions and maximum saturation current tolerances for the magnetic core over an airgap of 150 mm were carried out. Likewise, parametric performance evaluations of the different resonant coil designs in three-dimensional space comprising of airgap variation, longitudinal and lateral misalignment were undertaken. From the FEA and Parametric performance results, the model of an optimal design was evaluated through simulation and was found to achieve a strong magnetic coupling factor of more than 0.5 across an airgap of 170 mm

MLSys: The New Frontier of Machine Learning Systems

Machine learning (ML) techniques are enjoying rapidly increasing adoption. However, designing and implementing the systems that support ML models in real-world deployments remains a significant obstacle, in large part due to the radically different development and deployment profile of modern ML methods, and the range of practical concerns that come with broader adoption. We propose to foster a new systems machine learning research community at the intersection of the traditional systems and ML communities, focused on topics such as hardware systems for ML, software systems for ML, and ML optimized for metrics beyond predictive accuracy. To do this, we describe a new conference, MLSys, that explicitly targets research at the intersection of systems and machine learning with a program committee split evenly between experts in systems and ML, and an explicit focus on topics at the intersection of the two

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This paper formulates and shows how to solve the problem of selecting the cache size and depth of cache pipelining that maximizes the performance of a given instruction-set architecture. The solution combines trace-driven architectural simulations and the timing analysis of the physical implementation of the cache. Increasing cache size tends to improve performance but this improvement is limited because cache access time increases with its size. This trade-off results in an optimization problem we referred to as multilevel optimization, because it requires the simultaneous consideration of two levels of machine abstraction: the architectural level and the physical implementation level. The introduction of pipelining permits the use of larger caches without increasing their apparent access time, however the bubbles caused by load and branch delays limit this technique. In this paper we also show how multilevel optimization can be applied to pipelined systems if software- and hardware-based strategies are considered for hiding the branch and load delays. The multilevel optimization technique is illustrated with the design of a pipelined cache for a high clock rate MIPS-based architecture. The results of this design exercise show that

Bayesian Optimization with a Prior for the Optimum

While Bayesian Optimization (BO) is a very popular method for optimizing expensive black-box functions, it fails to leverage the experience of domain experts. This causes BO to waste function evaluations on bad design choices (e.g., machine learning hyperparameters) that the expert already knows to work poorly. To address this issue, we introduce Bayesian Optimization with a Prior for the Optimum (BOPrO). BOPrO allows users to inject their knowledge into the optimization process in the form of priors about which parts of the input space will yield the best performance, rather than BO’s standard priors over functions, which are much less intuitive for users. BOPrO then combines these priors with BO’s standard probabilistic model to form a pseudo-posterior used to select which points to evaluate next. We show that BOPrO is around 6.67 × faster than state-of-the-art methods on a common suite of benchmarks, and achieves a new state-of-the-art performance on a real-world hardware design application. We also show that BOPrO converges faster even if the priors for the optimum are not entirely accurate and that it robustly recovers from misleading priors

O.A. Olukotun

This paper formulates and shows how to solve the problem of selecting the cache size and depth of cache pipelining that maximizes the performance of a given instruction-set architecture. The solution combines trace-driven architectural simulations and the timing analysis of the physical implementation of the cache. Increasing cache size tends to improve performance but this improvement is limited because cache access time increases with its size. This trade-off results in an optimization problem we referred to as multilevel optimization, because it requires the simultaneous consideration of two levels of machine abstraction: the architectural level and the physical implementation level. The introduction of pipelining permits the use of larger caches without increasing their apparent access time, however the bubbles caused by load and branch delays limit this technique. In this paper we also show how multilevel optimization can be applied to pipelined systems if software- and hardware-b..