Error detection for PHEV,BEV and stationary battery systems

Battery cells being electrically disconnected resulting from degradation, mechanical stress, or corrosion can lead to hazardous situations during operation of electric vehicles or storage systems in stationary applications. The mentioned errors can be acceptable in some cases when cells or cell strings are connected in parallel, but the failure is to be detected in order to guarantee the reliable and safe operation of the battery system. A method enabling the estimation whether individual battery cells are faulty (cell error or electrically disconnected) by evaluating the mean impedance and capacity information of cell groups is introduced and validated.     

Dynamic fuel cell gas humidification system

Water management is one of the crucial factors regarding the performance and durability of low temperature PEM fuel cells. Amongst other factors, the water balance in an operating fuel cell can be influenced by the humidification of the reaction gases. For transient response investigations of the fuel cell behavior under fast humidification changes a system is needed which is able to humidify the supplied gases in a highly dynamic and reproducible way. Exact knowledge of the water content of the supplied gases is of utmost importance to study humidification effects. In this contribution, a dynamic fuel cell humidification system is presented. Reliability of the concept is proven by using three different methods: straightforward dew point measurements, electrochemical impedance spectroscopy (EIS) and in situ neutron radiography. The test setup is able to provide dew point temperatures with a tolerance range of 1–3 K leading to a highly reproducible fuel cell performance and water content of the complete cell.     

I2VM: Incremental import vector machines

We introduce an innovative incremental learner called incremental import vector machines (I²VM). The kernel-based discriminative approach is able to deal with complex data distributions. Additionally, the learner is sparse for an efficient training and testing and has a probabilistic output. We particularly investigate the reconstructive component of import vector machines, in order to use it for robust incremental learning. By performing incremental update steps, we are able to add and remove data samples, as well as update the current set of model parameters for incremental learning. By using various standard benchmarks, we demonstrate how I²VM is competitive or superior to other incremental methods. It is also shown that our approach is capable of managing concept-drifts in the data distributions.     

Development of a wind turbine gearbox virtual load sensor using multibody simulation and artificial neural networks

A current development trend in wind energy is characterized by the installation of wind turbines (WT) with increasing rated power output. Higher towers and larger rotor diameters increase rated power leading to an intensification of the load situation on the drive train and the main gearbox. However, current main gearbox condition monitoring systems (CMS) do not record the 6‑degree of freedom (6-DOF) input loads to the transmission as it is too expensive. Therefore, this investigation aims to present an approach to develop and validate a low-cost virtual sensor for measuring the input loads of a WT main gearbox. A prototype of the virtual sensor system was developed in a virtual environment using a multi-body simulation (MBS) model of a WT drivetrain and artificial neural network (ANN) models. Simulated wind fields according to IEC 61400‑1 covering a variety of wind speeds were generated and applied to a MBS model of a Vestas V52 wind turbine. The turbine contains a high-speed drivetrain with 4‑points bearing suspension, a common drivetrain configuration. The simulation was used to generate time-series data of the target and input parameters for the virtual sensor algorithm, an ANN model. After the ANN was trained using the time-series data collected from the MBS, the developed virtual sensor algorithm was tested by comparing the estimated 6‑DOF transmission input loads from the ANN to the simulated 6‑DOF transmission input loads from the MBS. The results show high potential for virtual sensing 6‑DOF wind turbine transmission input loads using the presented method.

     

A comparative study of the corrosion stability of dental amalgams with electrochemical impedance measurements

The corrosion susceptibility of a selection of amalgams used in dentistry has been examined with the electrochemical impedance method. The results are compared with data derived from cyclic voltammetry performed with these materials before. Most examined materials including a conventional amalgam show similar corrosion resistance; however, only one product shows a significantly higher corrosion resistance.     

Corrosion of nonprecious metal alloys in dentistry in the presence of common saliva additives

Corrosion stability of metallic materials used in dentistry is a major concern; identification of materials combining high stability and good performance is needed. The corrosion resistance of representative nonprecious metal alloys frequently used in dentistry in contact with artificial saliva solution with various added substances encountered in foodstuffs and in materials used in dentistry, possibly influencing the corrosion has been studied in vitro with electrochemical impedance measurements. Values of obtained corrosion resistances are interpreted in terms of conceivable effects of the additives on the rate of corrosion; they are also compared with previous results obtained with these alloys and additives using breakthrough electrode potentials obtained from slow scan cyclic voltammetry reported before.     

Simple high-performance liquid chromatographic method for the detection of phenylpropionylglycine in urine as a diagnostic tool in inherited medium-chain acyl-coenzyme A dehydrogenase deficiency

Deficiency of medium-chain acyl-CoA dehydrogenase is a frequent and treatable metabolic defect, which can be diagnosed by detection of phenylpropionylglycine in urine after an oral load of phenylpropionic acid. We studied the determination of phenylpropionylglycine in urine by isocratic ion-exclusion chromatography on a cation-exchange column using water-sulphuric acid (pH values between 2 and 4) as mobile phase. Phenylpropionylglycine, phenylpropionic acid and hippuric acid exhibited high retention factors with only a slight decline at increasing solvent pH. This resulted in a good separation from interfering substances after direct injection of urine. We hypothesize that pi-pi interactions between the aromatic carbonic acids and the ion-exchange resin are responsible for the strong retention on the stationary phase. We conclude that, even in asymptomatic patients, determination of phenylpropionylglycine in urine after a phenylpropionic acid load by ion-exclusion chromatography is a rapid and reliable diagnostic tool for the detection of medium-chain acyl-CoA dehydrogenase deficiency.     

Dysthyroid ophthalmopathy misinterpreted as ocular myositis

A 25-year-old female patient underwent surgery for a history of pain and popping on the lateral aspect of her right knee. It was initially thought that the patient had iliotibial (IT) band syndrome which was refractory to conservative treatment. However, upon release of the IT band, the snapping which was audible and palpable pre-operatively was still present. Further exploration of the posterior-lateral aspect of the knee revealed that the popliteal tendon was snapping over the incisura poplitea extensoria on the lateral femoral condyle. Excision of the prominent portion of the articular ridge below the sulcus popliteus eliminated the snapping sensation. The patient has remained asymptomatic since surgery for the past 22 months.     

Hybrid cutting of granite by use of ultrasonic assistance

Hybrid technologies offer an important approach to enhance existing limits of conventional cutting manufacturing processes. Superposition of the infeed with adapted ultrasonic vibrations enables reductions of machining forces. This results in diminished tool wear and longer tool life. Furthermore, an increase of removal rates can be achieved. Successful machining of recalcitrant metal-based materials by ultrasonic assisted systems creates a high potential to gain similar effects in machining of mineral-based materials. This will be studied in this article. The state of the art for the machining of stone uses geometrically undefined cutting edges. This paper focuses on the geometrically defined cutting of granite with additional ultrasonic assistance. Cutting tests at a test station with linear cutting motion are being performed. The ultrasonic frequency is maintained at 20 kHz. Different oscillation amplitudes are applied to influence process forces and the wear of the used carbide metal and polycrystalline diamond cutting segments (PCD). A method to observe the wear is developed by use of a stereomicroscope and a 3D measurement system. This will enable conclusions about the applicability of the geometry of the cutting segments and the process parameters. Due to the significant different wear rates of both cutting materials, the cutting force progression by using PCD tools shows completely different characteristics compared to the machining with carbide metal tools.