Hybrid Output Voltage Modulation (PWM-FSHE) for a Modular Battery System Based on a Cascaded H-Bridge Inverter for Electric Vehicles Reducing Drivetrain Losses and Current Ripple

This paper shows a preliminary study about the output voltage modulation of a modular battery system based on a seven-level cascaded H-bridge inverter used for vehicle propulsion. Two generally known modulation techniques, pulse width modulation (PWM) and fundamental selective harmonic elimination (FSHE), are extensively compared for such an innovative modular battery system inverter considering EVs\u27 broad torque-speed range. The inverter and the battery losses, as well as the inverter-induced current THD, are modeled and quantified using simulations. At low speeds, if the modulation index M is below 0.3, FSHE induces a high current THD (>>5%) and, thus, cannot be used. At medium speeds, FSHE reduces the drivetrain losses (including the battery losses), while operating at higher speeds, it even reduces the current THD. Thus, an individual boundary between multilevel PWM and FSHE can be determined using weightings for efficiency and current quality. Based on this, a simple hybrid modulation technique is suggested for modular battery system inverters, improving the simulated drive cycle efficiency by a maximum of 0.29% to 0.42% for a modeled small passenger vehicle. Furthermore, FSHE\u27s high speed dominance is demonstrated using a simple experimental setup with an inductive load

Exponential Modular Multilevel Converter for Low Voltage Applications

This paper presents the structure and control of a single phase Exponential Modular Multilevel Converter (EMMC), which works as a bidirectional AC/DC converter. In addition to the main H-bridge converter, it uses series connected H-bridges with DC link capacitors. The nominal voltage rating of the capacitors is increased with each module by factor of two. In this manner, the number of output voltage levels exponentially increases with the number of series connected H-bridges. By using low-voltage MOSFETs it is possible to achieve a very high efficiency, especially at partial loading. The high number of voltage levels reduces the output voltage THD, while using a low switching frequency. Thus, the required grid filter size can be substantially reduced. Furthermore, the additional capacitor modules increase the nominal output voltage at the AC side, so that the flow of the active and reactive power can be dynamically adjusted. Therefore, the EMMC could be used, for instance, as a vehicle charger directly connected to the grid

Battery Modeling and Parameter Extraction for Drive Cycle Loss Evaluation of a Modular Battery System for Vehicles Based on a Cascaded H-Bridge Multilevel Inverter

This article deals with the modeling and the parameterization of the battery packs used in cascaded H-bridge multilevel propulsion inverters. Since the battery packs are intermittently conducting the motor currents, the battery cells are stressed with a dynamic current containing a substantial amount of low-order harmonic components up to a couple of kHz, which is a major difference in comparison to a traditional two-level inverter drive. Different models, such as pure resistive and dynamic RC -networks, are considered to model the energy losses for different operating points (OPs) and driving cycles. Using a small-scale setup, the models’ parameters are extracted using both a low-frequency, pulsed current, and an electrochemical impedance spectroscopy (EIS) sweep. The models are compared against measurements conducted on the small-scale setup at different OPs. Additionally, a drive cycle loss comparison is simulated. The simple resistive model overestimates the losses by about 20% and is, thus, not suitable. The dynamic three-time-constant model, parameterized by a pulsed current, complies with the measurements for all analyzed OPs, especially at low speed, with a maximum deviation of 3.8%. Extracting the parameters using an EIS seems suitable for higher speeds, though the losses for the chosen OPs are underestimated by 1.5%–7.9%

Overview of Battery Impedance Modeling Including Detailed State-of-the-Art Cylindrical 18650 Lithium-Ion Battery Cell Comparisons

Electrical models of battery cells are used in simulations to represent batteries\u27 behavior in various fields of research and development involving battery cells and systems. Electrical equivalent circuit models, either linear or nonlinear, are commonly used for this purpose and are presented in this article. Various commercially available cylindrical, state-of-the-art lithium-ion battery cells, both protected and unprotected, are considered. Their impedance properties, according to four different equivalent circuit models, are measured using electrochemical impedance spectroscopies. Furthermore, the pricing, impedance, specific energy, and C-rate of the chosen battery cells are compared. For example, it is shown that the energy density of modern 18650 cells can vary from a typical value of 200 to about 260 Wh kg(-1), whereas the cell price can deviate by a factor of about 3 to 5. Therefore, as a result, this study presents a concise but comprehensive battery parameter library that should aid battery system designers or power electronic engineers in conducting battery simulations and in selecting appropriate battery cells based on application-specific requirements. In addition, the accuracies and computational efforts of the four equivalent circuit models are compared

Review of Technical Design and Safety Requirements for Vehicle Chargers and Their Infrastructure According to National Swedish and Harmonized European Standards

Battery electric vehicles demand a wide variety of charging networks, such as charging stations and wallboxes, to be set up in the future. The high charging power (typically in the range of a couple of kW up to a couple of hundred kW) and the possibly long duration of the charging process (up to more than 24 h) put some special requirements on the electrical infrastructure of charging stations, sockets, and plugs. This paper gives an overview of the technical design requirements and considerations for vehicle charging stations, sockets, and plugs, including their infrastructure, according to the Swedish Standard 4364000, "Low-voltage electrical installations-Rules for design and erection of electrical installations", and the corresponding harmonized European standards. In detail, the four internationally categorized charging modes are explained and the preferable charging plugs, including their two-bus communication, according to European Directives are shown. The dimensioning of the supply lines and the proper selection of the overcurrent protection device, the insulation monitor, and the residual current device are described. Furthermore, a comprehensive overview of the required safety measures, such as the application of an isolation transformer or the implementation of an overvoltage protection mechanism, and the limits for conducted electromagnetic emissions, such as low-frequency harmonics or high-frequency (150 kHz to 108 MHz) emissions, are given

Online and On-Board Battery Impedance Estimation of Battery Cells, Modules or Packs in a Reconfigurable Battery System or Multilevel Inverter

This paper shows two approaches to determine the battery impedance of battery cells or battery modules when used in a reconfigurable battery system (RBS) or in any type of modular multilevel converter (MMC) for electric drive applications. A generic battery model is used and the concepts of the recursive time and frequency-domain parameter extraction, using a current step and an electrochemical impedance spectroscopy, are explained. Thus, it is shown and demonstrated that the balancing current of neighboring cells/modules ,when in parallel operation, can be used, similar to the time-domain parameter extraction utilizing a current step, to determine the battery parameters. Furthermore, it is shown and demonstrated that a part of the inverter can be used as variable AC voltage source to control a sinusoidal current through the motor inductances of the drive train, which can be injected to the inserted battery cells/modules of an adjacent phase to perform an on-board impedance spectroscopy. Using either of the two presented approaches, the individual battery impedances can be easily determined, yielding the state of health (SOH) and the power capability of individual battery cells/modules. Nonetheless, the analyzed approaches were just considered to be applied at machine standstill, which is not suitable for grid-tied applications

Sensorless Capacitor Voltage Balancing of a Grid-Tied, Single-Phase Hybrid Multilevel Converter with Asymmetric Capacitor Voltages using Dynamic Programming

This paper shows a sensorless capacitor voltage balancing control approach for a grid-connected, single-phase hybrid multilevel inverter based on an NPC main stage with a voltage stiff DC-link and an arbitrary number of H-Bridge modules (capacitor modules) with asymmetric capacitor voltages. Using nearest-level control, a model predictive control (MPC) approach with a prediction horizon of one time step is chosen to find an optimal switching-state combination among the redundant switching combinations to balance the capacitor voltages as quick as possible. Using the Lyapunov stability criterion, it is shown that an offline calculated optimal switching-state sequence for each discrete output voltage level can be used to operate the inverter without using any voltage sensors for the capacitor voltages. To validate the stability of the approach, a laboratory inverter with a resistive load is operated with the offline calculated optimal switching-state sequences and it is shown that the capacitor voltages converge to their desired reference voltages

Capacitor Voltage Balancing of a Grid-Tied, Cascaded Multilevel Converter with Binary Asymmetric Voltage Levels Using an Optimal One-Step-Ahead Switching-State Combination Approach†

This paper presents a novel capacitor voltage balancing control approach for cascaded multilevel inverters with an arbitrary number of series-connected H-Bridge modules (floating capacitor modules) with asymmetric voltages, tiered by a factor of two (binary asymmetric). Using a nearest-level reference waveform, the balancing approach uses a one-step-ahead approach to find the optimal switching-state combination among all redundant switching-state combinations to balance the capacitor voltages as quickly as possible. Moreover, using a Lyapunov function candidate and considering LaSalle\u27s invariance principle, it is shown that an offline calculated trajectory of optimal switching-state combinations for each discrete output voltage level can be used to operate (asymptotically stable) the inverter without measuring any of the capacitor voltages, achieving a novel sensorless control as well. To verify the stability of the one-step-ahead balancing approach and its sensorless variant, a demonstrator inverter with 33 levels is operated in grid-tied mode. For the chosen 33-level converter, the NPC main-stage and the individual H-bridge modules are operated with an individual switching frequency of about 1 kHz and 2 kHz, respectively. The sensorless approach slightly reduced the dynamic system response and, furthermore, the current THD for the chosen operating point was increased from 3.28% to 4.58% in comparison with that of using the capacitor voltage feedback

Capacitor Voltage Balancing of a Grid-Tied, Cascaded Multilevel Converter with Binary Asymmetric Voltage Levels Using an Optimal One-Step-Ahead Switching-State Combination Approach

This paper presents a novel capacitor voltage balancing control approach for cascaded multilevel inverters with an arbitrary number of series-connected H-Bridge modules (floating capacitor modules) with asymmetric voltages, tiered by a factor of two (binary asymmetric). Using a nearest-level reference waveform, the balancing approach uses a one-step-ahead approach to find the optimal switching-state combination among all redundant switching-state combinations to balance the capacitor voltages as quickly as possible. Moreover, using a Lyapunov function candidate and considering LaSalle’s invariance principle, it is shown that an offline calculated trajectory of optimal switching-state combinations for each discrete output voltage level can be used to operate (asymptotically stable) the inverter without measuring any of the capacitor voltages, achieving a novel sensorless control as well. To verify the stability of the one-step-ahead balancing approach and its sensorless variant, a demonstrator inverter with 33 levels is operated in grid-tied mode. For the chosen 33-level converter, the NPC main-stage and the individual H-bridge modules are operated with an individual switching frequency of about 1 kHz and 2 kHz, respectively. The sensorless approach slightly reduced the dynamic system response and, furthermore, the current THD for the chosen operating point was increased from 3.28 to 4.58 in comparison with that of using the capacitor voltage feedback

Data Augmentation and Feature Selection for the Prediction of the State of Charge of Lithium-Ion Batteries Using Artificial Neural Networks

Lithium-ion batteries are a key technology for the electrification of the transport sector and the corresponding move to renewable energy. It is vital to determine the condition of lithium-ion batteries at all times to optimize their operation. Because of the various loading conditions these batteries are subjected to and the complex structure of the electrochemical systems, it is not possible to directly measure their condition, including their state of charge. Instead, battery models are used to emulate their behavior. Data-driven models have become of increasing interest because they demonstrate high levels of accuracy with less development time; however, they are highly dependent on their database. To overcome this problem, in this paper, the use of a data augmentation method to improve the training of artificial neural networks is analyzed. A linear regression model, as well as a multilayer perceptron and a convolutional neural network, are trained with different amounts of artificial data to estimate the state of charge of a battery cell. All models are tested on real data to examine the applicability of the models in a real application. The lowest test error is obtained for the convolutional neural network, with a mean absolute error of 0.27%. The results highlight the potential of data-driven models and the potential to improve the training of these models using artificial data