Representative Operating Points Research Articles

Hydrodynamic optimization of pump-turbine runner

The paper suggests the approach to automatic CFD-based optimization of the pump-turbine runner. An in-house 3D flow solver CADRUN is used for the solution of steady-state RANS equations and evaluation of objective functions in representative operating points of turbine and pump operating regimes. Both efficiency and cavitation characteristics are taken into account. Two approaches have been considered, resulting in 4- and 3-objective shape optimization problems. These problems were solved using multi-objective genetic algorithm. It was shown that the obtained optimized runners feature increased efficiency both in turbine and pump mode with cavitation performance, similar to that of the initial runner.

Experimental analysis of engine out emissions of a light-duty diesel engine during warm-up under cold start conditions

Emission targets of diesel engines are achieved by high-performance exhaust gas aftertreatment systems (EATS). Due to the light-off temperature, the system does not work as desired under cold operating conditions. This is especially challenging with the introduction of Euro 7 because engine warm up is getting more critical, as not only emission limits are getting tighter, but also the range of ambient temperatures is widened. Especially cold start conditions will be challenging: On one hand engine out emissions cannot be converted by the EATS before light-off which is extended by a greater temperature deficit. On the other hand, engine out emissions are affected by poor combustion boundary conditions. This paper focuses on the impact of temperature on emission formation by carrying out the first five km of three different driving cycles under cold start conditions. Based on these cycles, representative stationary operating points for each emission species were defined. A method was developed to reproduce thermal boundary conditions from engine warm up. This method allows to investigate the impact of thermal conditions on emission formation in steady state. Therefore a light-duty diesel engine was instrumented with a high number of temperature sensors in the cylinder liner wall and cylinder head as well as in the oil, gas, fuel and coolant path. The results were analyzed using 0D/1D simulation models to isolate the thermal impact on the emission formation. The obtained results serve as a basis for following measures on a similar single-cylinder research engine to develop innovative cold start measures.

Broadening Design and Optimization of High-Efficiency Region for a Dual-Mechanical-Port Flux-Switching Permanent Magnet Motor

In this article, a dual-mechanical-port flux-switching permanent magnet (DMP-FSPM) motor is studied for achieving high-efficiency design and optimization. The key of this study is to propose an optimization design approach for broadening high-efficiency region, where the motor efficiency fitting curve and the speed–torque envelope curve are combined. First, the efficiency function is established according to the motor power and loss equation. Then, high-efficiency region boundary points are obtained by combination of the fitted efficiency curve and speed–torque envelope curve. Next, the efficiency of representative operating points is determined and optimized to realize the broadening of motor high-efficiency region. Finally, the effectiveness of the proposed method and the studied DMP-FSPM motor is verified by the study results and experiment test.

UHBR Open-Test-Case Fan ECL5/CATANA

The application of composite fans enables disruptive design possibilities but increases sensitivity to multi-physical resonance between aerodynamic, structure dynamic and acoustic phenomena. As a result, aeroelastic problems increasingly set the stability limit. Test cases of representative geometries without industrial restrictions are a key element of an open scientific culture but are currently non-existent in the turbomachinery community. In order to provide a multi-physical validation benchmark representative of near-future UHBR fan concepts, the open-test-case fan stage ECL5 was developed at Ecole Centrale de Lyon. The design intention was to develop a geometry with high efficiency and a wide stability range that can be realized using carbon fibre composites. This publication aims to introduce the final test case, which is currently fabricated and will be experimentally tested. The fan blades are composed of a laminate made of unidirectional carbon fibres and epoxy composite plies. Their structural properties and the ply orientations are presented. To characterize the test case, details are given on the aerodynamic design of the whole stage, structure dynamics of the fan and aeroelastic stability of the fan. These are obtained with a state-of-art industrial design process: static and modal FEM, RANS and LRANS simulations. Aerodynamic analysis focuses on performance and shows critical flow structures such as tip leakage flow, radial flow migration and flow separations. Mechanical modes of the fan are described and discussed in the context of aeroelastic interactions. Their frequency distribution is validated in terms of resonance risk with respect to synchronous vibration. The aeroelastic stability of the fan is evaluated at representative operating points with a systematic approach. Potential instabilities are observed far from the operating line and do not compromise experimental campaigns.

The Calculation Method of Energy Consumption of Air-Conditioning System in Subway Vehicle Based on Representative Operating Points

In order to study the standard energy consumption of air-conditioning system of subway vehicle and optimize the performance of air-conditioning system, it is necessary to clarify the air-conditioning representative operating conditions. In this paper, based on the tested data during real operation of subway vehicle in summer, the characteristics of the air-conditioning operating conditions are analyzed, and the construction method of the operating conditions is first proposed. Secondly, taking the tested line as an example, using the constructed operating conditions as sample data, the k-means clustering algorithm is used to identify the representative operating points of the air-conditioning in the cooling season. Finally, the energy consumption based on the representative operating points of the cooling season is calculated by LMS AMEsim software, the error between calculated results and field measurements data is within 10%, which verifies the accuracy of energy consumption calculation method based on these representative operating points.

Fundamental Evaluation of Data Clustering Approaches for Driving Cycle-Based Machine Design Optimization

This article presents a fundamental evaluation of different clustering methods for analyzing driving cycles toward the efficient design of electric machines. It uses clusters of operating points to identify representative points (RPs) and the related optimization weights to design electric machines with optimal efficiency in the specific operating range. Typically, the design optimization of machines is carried out for one or a few speed–torque points. This article shows that for a predictable driving cycle or a specific set of operating points on the torque–speed plot, cluster analysis can be used to determine the representative operating points, which can be utilized in the optimization process to improve the overall efficiency for the considered driving cycle or operation profile. Furthermore, if multiphysics design is considered, the machine performance metrics can be guaranteed in multiple domains. This article presents a review of data clustering methods and their application in machine design optimization, where the pros and cons of the methods are weighed up. Further, X-Means method is proposed as an automated approach for cluster analysis and identification of RPs. In order to assess the effectiveness of the proposed method, a case study is carried out for the electromagnetic design of an interior permanent magnet (IPM) machine for the Worldwide harmonized Light vehicles Test Procedure (WLTP) driving cycle.

Experimental and numerical investigation of noise generation due to acoustic resonance in a cavitating valve

In order to study cavitation induced noise generation in a hydraulic system, cavitation is generated at a planar orifice. The sudden condensation (implosion) of vapor results in shock waves which excite the connected hydraulic pipes with pressure fluctuations. The synchronization between the continuous condensation and evaporation process and shock wave reflection can result in a stationary wave with superelevated pressure amplitudes. The fluid-borne sound is transferred through the mechanical structure into the air, where it can be perceived as a distracting whistling noise. A high-speed camera is used to visualize the void volume. Dynamic pressure signals are recorded in the vicinity of the orifice to analyze the pressure pulsation. The operating point is varied, the orifice geometry is changed and the reflection properties of the pipe on the up- and downstream sides are changed too. In addition, CFD (Computational Fluid Dynamics) simulations of the test bench are used to investigate the root cause of the whistling noise. With regards to representative operating points, the numerical results confirm the measured shedding vapor frequency, particularly the pressure pulsation frequency in the pipe and its amplitude. The conjunction of the experimental and numerical investigations provides the following findings: By reducing the discharge pressure, the void volume increases, which leads to a reduction of the resonance frequency of the pipe downstream of the orifice. For large void volumes, the pressure wave reflection at the void volume can be identified in the amplitude spectrum. The whistling noise depends on the history of the flow field. So, the increase and the reduction of the discharge pressure level leads to different whistling ranges. The whistling range decreases with the increasing length of the pipe resonator. Besides that, the order of the dominant resonance frequency increases. The experimental and numerical results indicate that the whistling noise only occurs, when the jet downstream of the orifice and hence the vapor is perpendicular to the sound propagation in the pipe resonator.

Computationally Efficient Optimization of a Five-Phase Flux-Switching PM Machine Under Different Operating Conditions

This paper investigates the comparative design optimizations of a five-phase outer-rotor flux-switching permanent magnet (FSPM) machine for in-wheel traction applications. To improve the comprehensive performance of the motor, two kinds of large-scale design optimizations under different operating conditions are performed and compared, including the traditional optimization performed at the rated operating point and the optimization targeting the whole driving cycles. Three driving cycles are taken into account, namely, the urban dynamometer driving schedule (UDDS), the highway fuel economy driving schedule (HWFET), and the combined UDDS/HWFET, representing the city, highway, and combined city/highway driving, respectively. Meanwhile, the computationally efficient finite-element analysis (CE-FEA) method, the cyclic representative operating points extraction technique, as well as the response surface methodology (in order to minimize the number of experiments when establishing the inverse machine model), are presented to reduce the computational effort and cost. From the results and discussion, it will be found that the optimization results against different operating conditions exhibit distinct characteristics in terms of geometry, efficiency, and energy loss distributions. For the traditional optimization performed at the rated operating point, the optimal design tends to reduce copper losses but suffer from high core losses; for UDDS, the optimal design tends to minimize both copper losses and PM eddy-current losses in the low-speed region; for HWFET, the optimal design tends to minimize core losses in the high-speed region; for the combined UDDS/HWFET, the optimal design tends to balance/compromise the loss components in both the low-speed and high-speed regions. Furthermore, the advantages of the adopted optimization methodologies versus the traditional procedure are highlighted.

Experimental investigation on RCCI heat transfer in a light-duty diesel engine with different fuels: Comparison versus conventional diesel combustion

Reactivity controlled compression ignition (RCCI) combustion has demonstrated to be able to avoid the NOx-soot trade-off appearing during conventional diesel combustion (CDC), with similar or better thermal efficiency than CDC under a wide range of operating conditions. The high thermal efficiency of RCCI is explained by the combination of a short-duration and well-phased combustion process, which maximizes the fuel-to-work conversion efficiency, together with relatively low combustion temperatures, which increases the specific heat ratio during expansion and reduces thermal gradients for heat transfer losses. The objective of this work is to study the RCCI heat transfer characteristics and compare them to those of the CDC regime. To do this, a single-cylinder light-duty research engine instrumented with 25 K-type thermocouples distributed among the cylinder head and cylinder liner is used. First, the influence of some engine settings on the RCCI heat transfer phenomenon is explored by means of parametric sweeps. Later, the RCCI heat transfer characteristics are compared for two different low reactivity fuels (LRF), gasoline and E85. Finally, the heat transfer characteristics of RCCI and CDC combustion regimes are compared at some representative operating points in matched load conditions. The results show that both LRF tested are suitable to be used in RCCI giving similar results in terms of energy usage. Moreover, the ability of RCCI combustion in exploiting the fuel energy to extract useful work is demonstrated, reducing by 13% the heat transfer versus CDC.

Iterative Approach for the Design of an Organic Rankine Cycle based on Thermodynamic Process Simulations and a Small-Scale Test Rig

Waste heat recovery from industrial processes may be a door opener for market penetration of Organic Rankine Cycle (ORC) systems. Within this study, an ORC for industrial waste heat recovery is designed by adopting an iterative approach. Therefore, experiments are performed in a thermal oil heated 1 kW test rig with internal recuperator and a maximum thermal efficiency of 10.6%. The results are iteratively implemented in thermodynamic process simulation. Thus, the simulation results of different stationary operating points can be compared to experimental measurements for different steps of the iterative design process. Results outline the importance of experimental results for the design of ORC systems. The simulation accuracy can be significantly improved with a single reimplementation of experimental data, which enables accurate sensitivity analysis on ORC waste heat recovery system performance. For two different representative operating points, the mean deviations between experiment and simulation decrease from 8.4% to 1.0% and 4.1% to 1.7% respectively, considering the enthalpy and pressure of all thermodynamic state points.

Novel Methodology for Selecting Representative Operating Points for the TNEP

As part of transmission network expansion planning (TNEP), a technical and economical assessment of several planning alternatives must be performed in order to ensure fulfillment of the network security criteria and to estimate the alternatives’ expected operating costs. This task requires performing load flow calculations for different operating points (OPs) of the power system. Due to the high computational burden, considering all possible OPs is simply not possible. As a consequence, only a set of representative OPs is usually taken into account. Most works in the TNEP focus on issues related to optimization algorithms and modeling, neglecting the selection process of the representative OPs. Furthermore, most works only consider a few OPs, providing little or no insight about the criteria used in the selection process or about the error made when evaluating planning alternatives using a limited number of OPs. In this work, a novel methodology for selecting representative OPs to consider within the TNEP is presented. The proposal pays special attention to critical situations, where the network security may be endangered. Furthermore, the methodology allows quantifying the error made when evaluating network operation using a limited number of representative OPs.

An Approach to an Optimal Design of Permanent Magnet Synchronous Machines for Battery Electric Vehicles

The described design of a permanent magnet synchronous motor for battery electric vehicles is based on a drive cycle. For a given vehicle a set of operating points of the electric machine can be derived from the cycle. The next step in the design of the traction motor is to find a suitable lamination layout. Common motor design procedures take only a few representative operating points into account. This paper describes an approach which includes a large number of operating points at early stages of the motor design process. It is based on a specialized motor model and an optimization strategy which are described in this paper. As an example a traction motor for the VW Golf CityStromer is designed by using the proposed method.

Choosing a Proper Control Structure for a Mechatronic System with Variable Parameters

The paper presents design methods and control structure solutions dedicated to servo systems with continuously variable parameters. In order to obtain high control performance for the strip winding system – speed control – four cascade control structures (CCS) (with a inner proportional-integral (PI) current controller) with bump-less switching between several control algorithms are developed and tested. These solutions prove simplicity in adaptation on the representative operating points. The current controller is tuned on the basis of the Modulus Optimum method (MO-m). The basic speed controllers are tuned by the Extended Symmetrical Optimum method (ESO-m) and the developed continuous-time speed controllers are discretized using Tustin's method. The developed speed controllers are: (1) a classical PI controller, (2) a Takagi-Sugeno PI fuzzy controllers (TS-PI-FCs), (3) a two-degree-of-freedom PID (2-DOF PID) and (4) a sliding mode (SM) PI quasi relay control solution. The cost-effective feature is ensured by simple controller design and easy implementation, and it is illustrated by a case study which includes simulation results. A process with variable inertia, variable reference and load disturbance is discussed due to its applicability as a controlled plant in the field of mechatronic systems.

Model-based fault diagnosis in electric drives using machine learning

Electric motor and power electronics-based inverter are the major components in industrial and automotive electric drives. In this paper, we present a model-based fault diagnostics system developed using a machine learning technology for detecting and locating multiple classes of faults in an electric drive. Power electronics inverter can be considered to be the weakest link in such a system from hardware failure point of view; hence, this work is focused on detecting faults and finding which switches in the inverter cause the faults. A simulation model has been developed based on the theoretical foundations of electric drives to simulate the normal condition, all single-switch and post-short-circuit faults. A machine learning algorithm has been developed to automatically select a set of representative operating points in the (torque, speed) domain, which in turn is sent to the simulated electric drive model to generate signals for the training of a diagnostic neural network, fault diagnostic neural network (FDNN). We validated the capability of the FDNN on data generated by an experimental bench setup. Our research demonstrates that with a robust machine learning approach, a diagnostic system can be trained based on a simulated electric drive model, which can lead to a correct classification of faults over a wide operating domain.

Estimation of the interpolation parameter in an interpolated model

We consider estimation of an interpolation parameter which represents the change of plant dynamics. The plant is described as a linear interpolation of proper stable coprime factorizations of two representative transfer function models identified at representative operating points. Observers for the representative models are employed in the estimation system. It is shown that the interpolation parameter can be computed using the deviations of the estimated outputs from the actual plant output. The estimated parameter is to be used in an interpolated controller.