Electric Endurance Research Articles

Ultrahigh energy density in dielectric nanocomposites by modulating nanofiller orientation and polymer crystallization behavior

High-energy density dielectrics for electrostatic capacitors are in urgent demand for advanced electronics and electrical power systems. Poly(vinylidene fluoride) (PVDF) based nanocomposites have attracted remarkable attention by intrinsic high polarization, flexibility, low density, and outstanding processability. However, it is still challenging to achieve significant improvement in energy density due to the common contradictions between electric polarization and breakdown strength. Here, we proposed a novel facile strategy that simultaneously achieves the construction of in-plane oriented BaTiO3 nanowires and crystallization modulation of PVDF matrix via an in-situ uniaxial stretch process. The polar phase transition and enhanced Young's modulus facilitate the synergetic improvement of electric polarization and voltage endurance capability for PVDF matrix. Additionally, the aligned distribution of nanowires could reduce the contact probability of nanowire tips, thus alleviating electric field concentration and hindering the conductive path. Finally, a record high energy density of 38.3 ​J/cm3 and 40.9 ​J/cm3 are achieved for single layer and optimized sandwich-structured nanocomposite, respectively. This work provides a unique structural design and universal method for dielectric nanocomposites with ultrahigh energy density, which presents a promising prospect of practical application for modern energy storage systems.

The integrated multi-performance fast optimization strategy for battery thermal management system

Increased battery energy density is required to boost electric vehicle endurance; however, this also raises the possibility of thermal runaway and power battery explosion. Improving the cooling system performance requires optimization and enhancement of classical systems. Traditional design approaches struggle to simultaneously enhance multiple aspects of performance, while an optimization based on Computational Fluid Dynamics (CFD) methods is often inefficient. Therefore, by integrating a flow resistance network model (FRNM) with a weighted average optimization algorithm (INFO), an efficient optimization for the comprehensive performance of the system can be achieved. Five optimized systems under different airflow rates were obtained through optimization. A comparison with two existing systems validated the effectiveness of the optimized system. The results demonstrate that, compared to the two reference systems, the optimized system decreases the maximum temperature difference by 65.51 % and 39.07 %, respectively. Furthermore, the improvement in temperature uniformity is more significant, increasing by 63.76 % and 34.40 %, respectively.

Model Predictive Control Strategies for Electric Endurance Race Cars Accounting for Competitors’ Interactions

Model Predictive Control Strategies for Electric Endurance Race Cars Accounting for Competitors’ Interactions

High Performance On-Chip Energy Storage Capacitors with Plasma-Enhanced Atomic Layer-Deposited Hf0.5Zr0.5O2/Al-Doped Hf0.25Zr0.75O2 Nanofilms as Dielectrics.

Concurrently achieving high energy storage density (ESD) and efficiency has always been a big challenge for electrostatic energy storage capacitors. In this study, we successfully fabricate high-performance energy storage capacitors by using antiferroelectric (AFE) Al-doped Hf0.25Zr0.75O2 (HfZrO:Al) dielectrics together with an ultrathin (1 nm) Hf0.5Zr0.5O2 underlying layer. By optimizing the Al concentration in the AFE layer with the help of accurate controllability of the atomic layer deposition technique, an ultrahigh ESD of 81.4 J cm-3 and a perfect energy storage efficiency (ESE) of 82.9% are simultaneously achieved for the first time in the case of the Al/(Hf + Zr) ratio of 1/16. Meanwhile, both the ESD and ESE exhibit excellent electric field cycling endurance within 109 cycles under 5~5.5 MV cm-1, and robust thermal stability up to 200 °C. Thus, the fabricated capacitor is very promising for on-chip energy storage applications due to favorable integratability with the standard complementary metal-oxide-semiconductor (CMOS) process.

Effect of Magnetic Field on Partial Discharge Dynamics in Insulation Systems of Transportation Power Devices

The globally observed trend toward electrically supplied devices is common in the transportation segment. Traditionally, the performance of electrical insulation has been assessed with respect to electric stresses and endurance. In all current-carrying devices, magnetic fields will also be superimposed on electric ones; therefore, the influence of a magnetic field’s exposure on partial discharge (PD) dynamics is an actual research topic. This problem is important in the transportation segment as well, where low- and medium-voltage levels are mostly used for supply and energy conversion (which are associated with high load currents). This article is focused on the influence of magnetic fields on the dynamics of PDs in the voids of insulation systems of transportation power devices and refers to both ac and dc cases. A rather weak magnetic field (80 mT) was established in order to detect and analyze early stages of PD behavior. The measurements of PDs that were carried out in a dedicated setup revealed their impact on PD intensity, which have been visualized in time-sequence diagrams and PD images. This detected effect is attributed to both the elongation of the charged particle trajectory and the enhancement of the electron energy due to acceleration. It has been shown that the impact of a magnetic field can be observed within a supply voltage frequency range of 20–400 Hz (which is typical for the transportation segment). The PD intensity was amplified in the above range at a magnetic field induction of 80 mT (even up to 50%). The effect of a magnetic field can be recognized as an additional modulation factor that influences the dynamics of PDs.

Maximum-distance race strategies for a fully electric endurance race car

This paper presents a bi-level optimization framework to compute the maximum-distance stint and charging strategies for a fully electric endurance race car. Thereby, the lower level computes the minimum-stint-time Powertrain Operation (PO) for a given battery energy budget and stint length, whilst the upper level leverages that information to jointly optimize the stint length, charge time and number of pit stops, in order to maximize the driven distance in the course of a fixed-time endurance race. Specifically, we first extend a convex lap time optimization framework to capture multiple laps and force-based electric motor models, and use it to create a map linking the charge time and stint length to the achievable stint time. Second, we leverage the map to frame the maximum-race-distance problem as a mixed-integer second order conic program that can be efficiently solved to the global optimum with off-the-shelf optimization algorithms. Finally, we showcase our framework on a 6 h race around the Zandvoort circuit. Our results show that a flat-out strategy can be extremely detrimental, and that, compared to when the stints are optimized for a fixed number of pit stops, jointly optimizing the stints and number of pit stops can increase the driven distance of several laps.

High Energy Storage Performance of All-Inorganic Flexible Antiferroelectric-Insulator Multilayered Thin Films.

With the increasingly high requirements for wearable and flexible devices, traditional inorganic capacitors cannot meet the flexible demand of next-generation electronic devices. In this work, the energy storage property of all-inorganic flexible films has been systematically studied. PbZrO3 (PZO) and Al2O3 (AO) are selected as the antiferroelectric layer and insulating layer, respectively. The heterostructured films are prepared on the fluorphlogopite (F-Mica) substrate by chemical solution deposition. The microstructure, polarization behavior, and energy storage performances are investigated. The results demonstrate that the AO/PZO/AO/PZO/AO (APAPA) multilayered thin film possesses a greatly improved energy storage density (Wrec) of 28.1 J/cm3 with an excellent energy storage efficiency (η) of 80.1%, which is ascribed to the enhanced breakdown strength and large difference in polarization. Furthermore, the capacitive films exhibit good stability under a wide working temperature range of 25-140 °C and an electric fatigue endurance of 107 cycles. Besides, the energy storage performances are almost unchanged after 104 bending cycles, demonstrating an excellent mechanical bending endurance. This work sheds light on the preparation technology and improvement of the dielectric energy storage performance for all-inorganic flexible multilayered thin films.

High energy storage performance for flexible PbZrO3 thin films by seed layer engineering

Antiferroelectric film capacitors have attracted increasing attention due to their excellent energy storage properties. In this work, PbZrO3 (PZO) antiferroelectric films have been prepared on the flexible fluorphlogopite (Mica) and rigid Pt/Ti/SiO2/Si substrates with a seed layer of LaNiO3 (LNO) layer by sol-gel process. The microstructure and energy storage properties of the films have been systematically studied. The results show that the Mica-Pt-LNO-PZO (M-LNO-PZO) thin film has an improved energy storage density (Wrec) of 16.6 J/cm3 with a charge and discharge efficiency (η) of 50.4%. Furthermore, the flexible thin films exhibit good stability under a wide working temperature range of 25–140 °C and an electric fatigue endurance of 107 cycles. Besides, the capacitive films can endure a bending radius of 4 mm and 104 bending cycles (@ r = 4 mm) with almost unchanged in the energy storage properties. The excellent energy storage properties endow inorganic thin films with great potential in flexible electronic devices.

Tip of the Iceberg: Optimal Drive Train Qualities for Experimental Electric Vehicles

The Electrathon is a competitive electric vehicle endurance race. Each team is given a 1000kWhr battery and one hour to travel the longest distance. Therefore, the vehicles design can have a very large impact on its performance. There is also be strategy involved, such as knowing when to overuse power or save power. There are a great number of design aspects that go into a vehicle, but one of most important components is the drive train. Optimizing the design of the single transmission drive train is vital to enhance the performance of the electric vehicle. Through various calculations, the end seems to show how a small sprocket ratio can allow for less power at faster speeds.

Improvement of Electric Aircraft Endurance through Propeller Optimization via BEM-CFD Methodology

An exhaustive optimization method is developed to minimize the power consumption for a propeller-driven electrical aircraft. The method finds the optimal value for a wide range of geometrical and operational parameters for a target thrust and airspeed. The optimization routine employs BEM for propeller predictions fed with aerodynamic airfoil data obtained from a proposed combined CFD-Montgomerie method which is also validated, furthermore several corrections to account for compressibility, three dimensional, viscous and Reynolds number effects are implemented. This BEM model showed an adequate fitting with experimental data. Additionally, Goldstein optimization via Vortex Theory is employed to design pitch and chord distributions minimizing the induced losses of the propeller. The optimization algorithm is validated through a study case where an existent optimization problem is approached leading to very similar results. Some trends and insights are obtained and discussed from the study case regarding the design of an optimal propulsion system. Finally, CFD simulations of the study case are carried out showing a slight relative error of BEM.

Field-Oriented Driving/Braking Control for Electric Vehicles

Most electric vehicles use regenerative brakes, since this kind of braking system design recycles electromotive force to increase electric power endurance during braking. This research proposes a sensor-free, integrated driving and braking control system that uses a space-vector-pulse-width module to synthesize stator current by purpose. It calculates the rotor position angle of the motor by detecting variation in the stator current and completes a closed-loop control. When the motor receives a brake command, the controller changes the inverter-switching sequence to generate reverse torque and a magnetic field to complete the driving or braking function using field-oriented control (FOC). This provides a smoother and more accurate motor control than sinusoidal commands with Hall feedback. Compared to the regenerative brake and rheostatic brake, the proposed braking system has a powerful braking torque and shorter reaction time. Comparisons of reaction times for a modified four-wheel electric vehicle equipped with a permanent magnet synchronous motor under neutral-sliding-status, FOC based braking, and short-circuit braking were conducted.

Big Data Mining Analysis of Key Indicators of Online New Energy Vehicles

In this paper, more than 300 new energy vehicle key indicators of online sales are mined, and big data visualization analysis is carried out. In October 2018, big data mining analysis was conducted on the brand, model, pure electric endurance, slow charging time, fast charging time, battery capacity, maximum power, maximum torque, monthly sales volume, annual cumulative sales volume, monthly transaction price, user score, number of public praise, manufacturer guidance price (low) and manufacturer guidance price (high) of each new energy vehicle market in Sina auto.com. The results show that the average pure electric endurance of new energy vehicles is 210.3 km (with a maximum endurance of 613 km), and the average fast charging time is 1.7 hours (with a minimum duration of half an hour). The best-known brand of new energy vehicles is BYD, with the highest market share of BYD and Toyota.

Synergy Effects in Electric and Hybrid Electric Aircraft

The interest in electric and hybrid electric power system has been increasing, in recent times, due to the benefits of this technology, such as high power-to-weight ratio, reliability, compactness, quietness, and, above all, elimination of local pollutant emissions. One of the key factors of these technologies is the possibility to exploit the synergy between powertrain, structure, and mission. This investigation addresses this topic by applying multi-objective optimization to two test cases — a fixed-wing, tail-sitter, Vertical Take-off and Landing Unmanned Aerial Vehicle (VTOL-UAV), and a Medium-Altitude Long-Endurance Unmanned Aerial Vehicle (MALE-UAV). Cruise time and payload weight were selected as goals for the first optimization problem, while fuel consumption and electric endurance were selected for the second one. The optimizations were performed with Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and S-Metric Selection Evolutionary Multiobjective Algorithm (SMS-EMOA), by taking several constraints into account. The VTOL-UAV optimization was performed, at different levels (structure only, power system only, structure and power system together). To better underline the synergic effect of electrification, the potential benefit of structural integration and multi-functionalization was also addressed. The optimization of the MALE-UAV was performed at two different levels (power system only, power system, and mission profile together), to explore the synergic effect of hybridization. Results showed that large improvements could be obtained, either in the first test case when, both, the powertrain design and the aircraft structure were considered, and in the optimization of the hybrid electric UAV, where the optimization of the aircraft flight path gave a strong contribution to the overall performances.

A method to analyze and optimize hybrid electric architectures applied to unmanned aerial vehicles

PurposeThis paper addressed some critical issues in the development of hybrid electric powertrains for aircraft and propose a design methodology based on multi-objective optimization algorithms and mission-based simulations.Design/methodology/approachScalable models were used for the main components of the powertrain, namely, the (two stroke diesel) engine, the (lithium) batteries and the (permanent magnet) motor. The optimization was performed with the NSGA-II genetic algorithm coupled with an in-house MATLAB tool. The input parameters were the size of engine, the hybridization degree and the specification of the battery (typology, nominal capacity, bus voltage, etc.). The outputs were electric endurance, additional volume, performance parameters and fuel consumption over a specified mission.FindingsElectric endurance was below 30 min in the two test cases (unmanned aerial vehicles [UAVs]) but, thanks to the recharging of the batteries on-board, the total electric time was higher. Fuel consumption was very high for the largest UAV, while an improvement of 11 per cent with respect to a conventional configuration was obtained for the smallest one.Research limitations/implicationsThe research used a simplified approach for flight mechanics. Some components were not sized in the proposed test cases.Practical implicationsThe results of the test cases stressed the importance of improving energy density and power density of the electric path.Social implicationsThe proposed methodology is aimed at minimizing the environmental impact of aircraft.Originality/valueThe proposed methodology was obtained from the automotive field with several original contributions to account for the aircraft application.

Electric Aircraft: Exploiting the Synergy between Powertrain, Energy Management and Structure

This study aims at investigating the synergy between powertrain and structure within the design process of a fixed-wing tail-sitter unmanned aerial vehicle (UAV). The UAV is equipped with a pure-electric power system and has vertical take-off and landing capabilities (VTOL). The problem is addressed by running a contemporary optimization of the parameters of both the powertrain and the UAV’s structure, in order to maximize electric endurance and payload weight through the usage of a performant multi-objective evolutionary algorithm named SMS-EMOA. Three different designs are selected, discussed and compared with literature results on the same UAV to quantify the increase of payload and cruise time that can be obtained by exploiting the synergy between structure and powertrain. The potentiality of furtherly improving payload through the usage of multi-functional panels, while keeping the same endurance, is also quantified and compared with the technologies proposed in literature.

Magnetic tunnel junction with Fe(001)/Co phthalocyanine/MgO(001) single-crystal multilayer

A single-crystal multilayer consisting of Fe, cobalt phthalocyanine (CoPc), and MgO was grown on an fcc-MgO(001) substrate. The reflection high-energy diffraction observation showed that the ultrathin fcc-MgO(001) film could be grown on bcc-Fe(001)/CoPc when the thickness of CoPc was less than 0.7 nm (about two molecular layers). A tunnel junction with a bcc-Fe(001)/CoPc/fcc-MgO(001)/bcc-Fe(001) layer achieved a tunnel magnetoresistance of about 20% and an electric field endurance of more than 1 V/nm at room temperature. The novel multilayer in the present study will enable us to advance the frontiers of molecular spintronics.

Fuel economy of hybrid electric flight

The present investigation addresses the problem of evaluating the endurance of hybrid electric aircraft and discusses the effect of battery specifications and the engine working points on fuel economy. In particular, the endurance per unit mass of fuel of a hybrid power system is calculated by assuming a constant power-level flight performed with alternate cycles of battery charging and discharging (ON-OFF strategy). The computation of the fuel economy requires accurate models for the time, the power and the energy associated with battery charging and discharge processes. In order to reach this goal, two approaches proposed in literature to evaluate electric endurance were discussed, amended and validated through comparison with experimental data. A model for constant-current/constant voltage battery charge was also presented and validated with literature experimental data. In order to explain how these models can be applied to real applications, a parallel hybrid power system was sized and analyzed for a medium-altitude long-endurance unmanned aerial vehicle. Lithium polymer batteries and two stroke diesel engines were considered and three different hybridization degrees were analyzed. The results showed a trade-off between electric flight time and overall endurance per unit mass of fuel and an improvement up to 12% in fuel consumption with respect to a non-hybrid case with the same engine.

Detection of resistive switching behavior based on the Al2O3/ZnO/Al2O3 structure with alumina buffers

The single ZnO layer and a sandwich Al2O3/ZnO/Al2O3 structure were prepared via atomic layer deposition, and the single ZnO layer showed a feature of ohmic conduction only. When we added that together with top and bottom alumina buffers, a non-polar resistive switching (RS) behavior was accomplished, allowing investigation of its electric endurance and retention characteristics. Analysis of the conduction mechanism at both high and low resistance states using auxiliary mathematic tools resulted in the proposed model of conducting filaments formed in the insulating Al2O3 buffers. The effect of stopping voltage Vend on the resistance window at high resistance state is studied and discussed.

Three-dimensional particle simulation of back-sputtered carbon in electric propulsion test facility

The back-sputtering deposition on thruster surface caused by ion bombardment on chamber wall material affects the performance of thrusters during the ground based electric propulsion endurance tests. In order to decrease the back-sputtering deposition, most of vacuum chambers applied in electric propulsion experiments are equipped with anti-sputtering targets. In this paper, a three-dimensional model of plume experimental system (PES) including double layer anti-sputtering target is established. Simulation cases are made to simulate the plasma environment and sputtering effects when an ion thruster is working. The particle in cell (PIC) method and direct simulation Monte Carlo (DSMC) method is used to calculate the velocity and position of particles. Yamamura's model is used to simulate the sputtering process. The distribution of sputtered anti-sputtering target material is presented. The results show that the double layer anti-sputtering target can significantly reduce the deposition on thruster surface. The back-sputtering deposition rates on thruster exit surface for different cases are compared. The chevrons on the secondary target are rearranged to improve its performance. The position of secondary target has relation with the ion beam divergence angle, and the radius of the vacuum chamber. The back-sputtering deposition rate is lower when the secondary target covers the entire ion beam.

High Electric Field Carrier Transport and Power Dissipation in Multilayer Black Phosphorus Field Effect Transistor with Dielectric Engineering

This study addresses high electric field transport in multilayer black phosphorus (BP) field effect transistors with self‐heating and thermal spreading by dielectric engineering. Interestingly, a multilayer BP device on a SiO2 substrate exhibits a maximum current density of 3.3 × 1010 A m−2 at an electric field of 5.58 MV m−1, several times higher than multilayer MoS2. The breakdown thermometry analysis reveals that self‐heating is impeded along the BP–dielectric interface, resulting in a thermal plateau inside the channel and eventual Joule breakdown. Using a size‐dependent electro‐thermal transport model, an interfacial thermal conductance of 1–10 MW m−2 K−1 is extracted for the BP–dielectric interfaces. By using hexagonal boron nitride (hBN) as a dielectric material for BP instead of thermally resistive SiO2 (κ ≈ 1.4 W m−1 K−1), a threefold increase in breakdown power density and a relatively higher electric field endurance is obtained together with efficient and homogenous thermal spreading because hBN has superior structural and thermal compatibility with BP. The authors further confirm the results based on micro‐Raman spectroscopy and atomic force microscopy, and observe that BP devices on hBN exhibit centrally localized hotspots with a breakdown temperature of 600 K, while the BP devices on SiO2 exhibit hotspots in the vicinity of the electrode at 520 K.