Emulation of an electric machine allows the testing of a drive inverter and controller of an electric drive system, prior to the manufacture of a machine prototype. This paper presents the emulation of a variable flux machine (VFM). The VFM emulator system proposed in this paper uses a detailed look-up table-based machine model for the purpose of emulation. This allows the emulator to mimic all machine magnetic and geometric behaviors such as saturation and torque ripple. In addition, the machine emulator proposed in this paper uses high-performance high-bandwidth linear amplifiers as power amplifiers. This enables a high bandwidth; leading to a high accuracy machine emulation. A detailed control description for the proposed machine emulator system and a machine model look-up table data verification against a prototype machine is initially presented. Experimental results are then presented to validate the utility of the proposed VFM emulator system to emulate various machine transient behaviors at different magnetization levels. Experimental results obtained from the emulator are subsequently compared against the experimental results obtained from a prototype VFM drive to verify the emulation accuracy.

Linear Amplifier-Based Power-Hardware-in-the-Loop Emulation of a Variable Flux Machine

Cell balancing is a vital function of battery management system (BMS), which is implemented to extend the battery run time and service life. Various cell balancing techniques are being focused due to the growing requirements of larger and superior performance battery packs. The passive balancing approach is the most popular because of its low cost and easy implementation. As the balancing energy is dissipated as heat by the balancing resistors, an appropriate thermal scheme of the balancing system is necessary, to keep the BMS board temperature under a tolerable limit. In this paper, optimum selection of balancing resistor with respect to degree of cell imbalance, balancing time, C- rate, and temperature rise using machine learning (ML) based balancing control algorithm is proposed to improve the balancing time and optimal power loss management. Variable resistors are utilised in the passive balancing system, in order to optimize the power loss and to obtain optimal thermal characterization. The performance of the proposed system is evaluated using back propagation neural network (BPNN), radial basis neural network (RBNN), and long short term memory (LSTM). Error analysis of the balancing system is done to optimize balancing parameters and the proposed algorithms are compared using performance indices such as mean square error (MSE), root mean square error (RMSE), and mean absolute error (MAE) to validate the balancing model performance. The possible optimization scope for implementing passive balancing using machine learning algorithms are experimented in the Matlab-Simscape environment.

/pdf/machine-learning-based-optimal-cell-balancing-mechanism-for-3ejunv7awb.pdf

Machine Learning-Based Optimal Cell Balancing Mechanism for Electric Vehicle Battery Management System

Power-hardware-in-the-loop (PHIL) simulations, in the form of machine emulation, are gaining popularity for electric drive system testing in transportation applications. Since there is a reduced chance of equipment damage with PHIL simulations, they are particularly suited for the testing of electric drive systems, for drive inverter faults. This article investigates PHIL simulations to emulate machine behavior in the event of drive inverter faults resulting due to a gate-drive failure of one or more switches. Modifications are proposed to the closed-loop current control of the machine emulator system. These modifications ensure that various lower order harmonics in the emulated machine currents, resulting due to the drive inverter faults, are accurately emulated. Drive inverter damages resulting due to machine behavior emulation in fault conditions are avoided by proposing appropriate emulator control structure modifications. Experimental results are obtained for the emulation of machine behavior for various drive inverter gate-drive faults. These experimental results are compared with that obtained from a faulty drive inverter feeding a prototype machine. A close match between the two results is shown to prove the sufficiency and utility of the proposed controller modifications in the developed PHIL-based machine emulation system.

An Investigation of Power-Hardware-in-the-Loop- Based Electric Machine Emulation for Driving Inverter Open-Circuit Faults

The use of Hardware-in-the-Loop (HIL) systems implemented in Field Programmable Gate Arrays (FPGAs) is constantly increasing because of its advantages compared to traditional simulation techniques. This increase in usage has caused new challenges related to the improvement of their performance and features like the number of output channels, while the price of HIL systems is diminishing. At present, the use of low-speed Digital-to-Analog Converters (DACs) is starting to be a commercial possibility because of two reasons. One is their lower price and the other is their lower pin count, which determines the number and price of the FPGAs that are necessary to handle those DACs. This paper compares four filtering approaches for providing suitable data to low-speed DACs, which help to filter high-speed input signals, discarding the need of using expensive high-speed DACS, and therefore decreasing the total cost of HIL implementations. Results show that the selection of the appropriate filter should be based on the type of the input waveform and the relative importance of the dynamics versus the area.

https://www.mdpi.com/2079-9292/8/10/1116/pdf

A Comparison of Filtering Approaches Using Low-Speed DACs for Hardware-in-the-Loop Implemented in FPGAs

In this paper, the static and dynamic simulations, and mechanical-level Hardware-In-the-Loop (MHIL) laboratory testing methodology of prototype drive systems with energy-saving permanent-magnet electric motors, intended for use in modern construction cranes is proposed and described. This research was aimed at designing and constructing a new type of tower crane by Krupinski Cranes Company. The described research stage was necessary for validation of the selection of the drive system elements and confirmation of its compliance with applicable standards. The mechanical construction of the crane was not completed and unavailable at the time of testing. A verification of drive system parameters had to be performed in MHIL laboratory testing, in which it would be possible to simulate torque acting on the motor shaft. It was shown that the HIL simulation for a crane may be accurate and an effective approach in the development phase. The experimental tests of selected operating cycles of prototype crane drives were carried out. Experimental research was performed in the LINTE^2 laboratory of the Gdansk University of Technology (Poland), where the MHIL simulator was developed. The most important component of the system was the dynamometer and its control system. Specialized software to control the dynamometer and to emulate the load subjected to the crane was developed. A series of tests related to electric motor environmental parameters was carried out.

https://www.mdpi.com/1996-1073/13/21/5727/pdf

Mechanical-Level Hardware-In-The-Loop and Simulation in Validation Testing of Prototype Tower Crane Drives

The paper deals with the development of a Power Hardware-In-the-Loop (PHIL) simulator using parallel connected Active Neutral Point Clamped (ANPC) bridge arms. The parallel connection offers better emulation precision due to the increased number of available voltage levels and the higher apparent switching frequency. The concept to emulate the transient inductance and the inner voltage of an AC machine is introduced and analyzed in a single phase model using interleaved modulation in the parallel arms, and level shifted carriers for the upper and lower side of the arms. The static and dynamic precision of the emulation is influenced by the current balancing applied for distributing the power evenly on the parallel arms. A compromise is required to keep both the emulation and balancing error at low level.

Power HIL Emulation of AC Machines with Parallel Connected ANPC Bridge Arms

Multi-cell lithium-ion batteries must be balanced in order to avoid severe cell charge imbalances, which reduce the apparent capacity of the battery pack. Nowadays active balancing methods are gaining popularity in spite of having potential to result in less beneficial outcome in certain situations. In this paper a balancing design selection guide will be presented in an application oriented way. The importance of proper balancing strategy selection will be demonstrated with an in depth simulation of different passive and active designs.

Application Dependent Optimization of Balancing Methods for Lithium-ion Batteries

The advances in FPGA technology have enabled to develop fast HIL (Hardware-in-the-Loop) simulators, revolutionizing control software and hardware development for power electronics. HIL simulators should reproduce the same analogue signals that could be measured on real main circuits. A very common limitation in these applications is the usable pin count of the FPGA, therefore using the most pin-effective Digital-to-Analogue Converters (DACs) becomes critical. $\Sigma-\Delta$ DACs provide a simple, FPGA-synthesizable solution using a single pin for each output, but the output signal's bandwidth and latency is usually not sufficient, because of the required analogue filters. Higher order $\Sigma-\Delta$ DACs usually perform much better in the aspect of the Signal-to-Noise-Ratio (SNR) but not the usable bandwidth. This paper introduces a new bitstream DAC architecture based on the sliding mode control of the output analogue filter model. It is optimized mainly to reproduce current transducer signals in power electronics (usually triangle waves), which can be done more accurately than traditional $\Sigma-\Delta$ solutions.

FPGA-Driven DAC with Second Order Sliding Mode Control of Filter Model for Hardware-In-the-Loop Simulators

Nowadays, the need for isolated bidirectional DC-to-DC converters is increasing, as electric energy storage is gaining more popularity. For high power applications, the Dual Active Bridge (DAB) DC-to-DC converters are widely used. Various control methods were proposed throughout the years, but none of them is practical to use with low frequency and low leakage transformers. In this paper, a novel control algorithm is presented, which is specifically designed for these applications and has outstanding transient response characteristics. The behavior is analyzed and compared to Single Phase Shift control thorough hardware-in-the-loop simulation.

Szabolcs Vereb

Papers

Power HIL Emulation of AC Machines with Parallel Connected ANPC Bridge Arms

Application Dependent Optimization of Balancing Methods for Lithium-ion Batteries

FPGA-Driven DAC with Second Order Sliding Mode Control of Filter Model for Hardware-In-the-Loop Simulators

Cross-Period Single Phase Shift Control Technique for High Power and Low Frequency Dual Active Bridge Converters