Working Cycle Research Articles

Working cycle condition construction for electric wheel loader based on principal component analysis and cluster analysis

With the rapid development of new energy technology, cycle condition is significant for the design of powertrain system, whole machine economy, endurance, and other performance parameters of pure electric drive machines. Many cycle conditions of the passenger car industry have been defined. While that for the loader which has complex operation modes and working conditions, has less research on this aspect. Cycle conditions suitable for loader have not been constructed. To support the research and development of electric loader power system, the cycle conditions that can reflect the driving characteristics of electric loader are studied in this paper. According to the typical “V” cycle condition of loader, the actual driving condition data are collected and the kinematic segments are divided. The kinematic segments are grouped into five categories by using principal component analysis and K-means clustering algorithm to obtain the clustering center of each category. The working cycle condition is formed by extracting the combination of segments closest to the clustering center. Finally, based on AMESim simulation and whole machine test analysis, the error between the simulation and vehicle test results of the energy consumption is 3.4%. The accuracy and effectiveness of the proposed constructed cycle conditions are verified.

LoRaWAN for Vehicular Networking: Field Tests for Vehicle-to-Roadside Communication.

Vehicular wireless networks are one of the most valuable tools for monitoring platforms in the automotive domain. At the same time, Internet of Things (IoT) solutions are playing a crucial role in the same framework, allowing users to connect to vehicles in order to gather data related to their working cycle. Such tasks can be accomplished by resorting to either cellular or non-cellular wireless technologies. While the former can ensure low latency but require high running costs, the latter can be employed in quasi-real-time applications but definitely reduce costs. To this end, this paper proposes the results of two measurement campaigns aimed at assessing the performance of the long-range wide-area network (LoRaWAN) protocol when it is exploited as an enabling technology to provide vehicles with connectivity. Performances are evaluated in terms of packet loss (PL) and received signal strength indicator (RSSI) in wireless links. The two testing scenarios consisted of a transmitter installed on a motorbike running on an elliptical track and a receiver placed in the centre of the track, and a transmitter installed on the roof of a car and a receiver placed next to a straight road. Several speeds were tested, and all the spreading factors (SFs) foreseen by the protocol were examined, showing that the Doppler effect has a marginal influence on the receiving performance of the technology, and that, on the whole, performance is not significantly affected by the speed. Such results prove the feasibility of LoRaWAN links for vehicular network purposes.

Heat stress increases carbohydrate oxidation rates and oxygen uptake during prolonged load carriage exercise

ABSTRACT Military missions are conducted in a multitude of environments including heat and may involve walking under load following severe exertion, the metabolic demands of which may have nutritional implications for fueling and recovery planning. Ten males equipped a military pack loaded to 30% of their body mass and walked in 20°C/40% relative humidity (RH) (TEMP) or 37°C/20% RH (HOT) either continuously (CW) for 90 min at the first ventilatory threshold or mixed walking (MW) with unloaded running intervals above the second ventilatory threshold between min 35 and 55 of the 90 min bout. Pulmonary gas, thermoregulatory, and cardiovascular variables were analyzed following running intervals. Final rectal temperature (MW: p < 0.001, g = 3.81, CW: p < 0.001, g = 4.04), oxygen uptake, cardiovascular strain, and energy expenditure were higher during HOT trials (p ≤ 0.05) regardless of exercise type. Both HOT trials elicited higher final carbohydrate oxidation (CHOox) than TEMP CW at min 90 (HOT MW: p < 0.001, g = 1.45, HOT CW: p = 0.009, g = 0.67) and HOT MW CHOox exceeded TEMP MW at min 80 and 90 (p = 0.049, g = 0.60 and p = 0.024, g = 0.73, respectively). There were no within-environment differences in substrate oxidation indicating that severe exertion work cycles did not produce a carryover effect during subsequent loaded walking. The rate of CHOox during 90 minutes of load carriage in the heat appears to be primarily affected by accumulated thermal load.

Process Analysis and Modelling of Operator Performance in Classical and Digitalized Assembly Workstations

Strong competition in the automotive industry has required manufacturers to implement lean production, both with methods and techniques specific to Industry 4.0. At the same time, universities must provide graduates with specific skills for applying these new production methods and techniques. In this context, a lean learning factory was developed in the Pitesti University Center that allows students to learn about, experiment with, and research new lean manufacturing methods and techniques as well as Industry 4.0 in an environment similar to that of enterprises. The research presented in this study aimed to identify the minimum number of repetitions necessary to train operators to perform the same assembly operation while working at two differently organized workstations: one classic and the other including digital techniques. Several indicators were considered in our analysis, such as the number of errors, the number of stops, the effective duration of the work cycle, and the percentage ratio between the standard duration of cyclical activities and the effective duration of the work cycle. The evolution of these indicators was mathematically modelled by regression functions, using the least squares method. The obtained results also highlight the usefulness of applying the DOJO method as a lean-manufacturing-specific learning technique and the efficiency of implementing digital techniques in work organization.

A novel data fusion based intelligent identification approach for working cycle stages of hydraulic excavators

Accurately identifying the stage of the excavator working cycle is the prerequisite to achieve the staged energy-saving control. However, current identification methods often overlook the influence of hydraulic system latency on identification results and depend on a single model, resulting in poor generalization performance of the identification approaches. Moreover, expert calibration system remains a necessary factor for improving identification accuracy. Aiming at these issues, a hybrid multi-scale feature extractor and a decision-level data fusion classifier approach (HMSFE-DFC) is proposed to identify the working cycle stages of excavator. The input signal employs mixed signals from the main pump pressure and the control current of the proportional solenoid valve to reduce the response delay caused by the single main pump pressure signal. A hybrid multi-scale feature extractor is constructed using a convolutional neural network temporal self-attention feature extraction mechanism and one-dimensional ResNet-50 architecture to extract multiscale features. To prevent overfitting, a decision-level data fusion classifier is used to fuse the decisions information of numerous classifiers. The accuracy of stage identification for 10 consecutive working cycles reaches 95.21%, which verifies its effectiveness.

Estimation of Pro-Inflammatory Markers In Night Shift Healthcare Workers And Identify Risk Factors Associated With It

Shift labor, with hours outside of the regular diurnal work cycle, is used to facilitate round-the-clock emergency healthcare services. This impacts the circadian rhythm, which can potentially activate the pro-inflammatory responses of the immune system. This study aimed to find out the levels of pro-inflammatory markers in night shift healthcare workers and find risk factors associated with their increase. 303 participants (doctors, nurses, technicians, health care aids) were recruited with 169 participants nightshift and 134 dayshift workers. Pro-inflammatory markers Highly Sensitive C-Reactive Protein (hsCRP) and Total Leukocyte Count (TLC)] were estimated. Factors were compared by t test, Wilcoxon Rank Sum test and Chi square test. Risk factors for hsCRP elevation were identified by logistic regression analysis. Pro-inflammatory markers like hsCRP and TLC were significantly increased in night shift health workers in comparison to the day shift workers (hsCRP 0.30± 0.33 mg/dl vs 0.10± 0.09 mg/dl, TLC 8181.06± 1181.53 /cu mm vs 7473.80± 1018.81 /cu mm) respectively. Multivariate logistic regression analysis showed night shift work (OR 48.20 95% CI (4.99-465.61), age (OR 1.13 95% CI (1.01-1.26)) and BMI (OR 1.18 95% CI (1.06-1.32)) as independent predictors of elevated hsCRP after adjusting for other risk factors. Hence, night-shift work is an independent risk factor for a rise in pro-inflammatory markers. These findings might aid health care workers and policymakers strategize methods to tackle the challenges through providing support programs, counselling sessions to avoid ailments and deliver health services in a better way.

Study of operating modes of electromagnetic hammer with adjustable impact energy and blow frequency

The current work was designed to study the operating modes of electromagnetic impact mechanism (electromagnetic hammer) comprising idle and working stroke windings that are enclosed in magnetic conductor, and reciprocating ferromagnetic striker. Investigation was conducted by modelling in MATLAB environment and performing verification tests with different hammers. Simulation model of the hammer was derived using experimentally obtained static characteristic curves of flux linkage and thrust force for each of the windings. Results revealed that at maximum working stroke winding voltage-varying idle stroke winding voltage, the impact energy did not change, but the impact frequency varied between 0-187 bpm. At maximum idle stroke winding voltage and working stroke winding voltage ranging between 0 to maximum value, the impact energy varied between 84-360 J, the impact frequency varied between 96-187 bpm. Maximum losses over the working cycle were associated with electric losses in the hammer windings and can be reduced by reducing winding currents through increasing the striker speed. The mathematical model of the current study allowed quantifying energy parameters of the electromagnetic hammer. The impact machine cycle includes three operating modes, each determines the main energy parameters: efficiency, impact energy, and cycle time.

Justification the surface mining system parameters of amber pits with semi-mobile beneficiation plants

Research is aimed at establishing the dependence of the semi-mobile beneficiation plant productivity on the face width of the excavator at the developing amber deposits. Analytical research methods were used at the development of the methodology to determine the working time of excavator, taking into account the time for moving the enrichment plant. Appropriate calculation methods are relevant for determining the required amount of technical equipment that ensures the mining operation. The efficient parameters of the face width during the excavation of mining mass have been established, depending on the parameters of the excavator boom, taking into account its replacement. It was determined that the duration of the working cycle of working out the block with the corresponding face width of the pit is based on the time of loading and moving the semi-mobile beneficiation plant, as well as the time for reexcavation. The effective width of the working pit face was calculated with the appropriate choice of the excavator boom. The established parameters of the face width of the pit on the mining bench with the loading of mining mass to the semi-mobile concentrator were implemented in the pit at the development of the Galbin-24 amber deposit.

Assessment of the Impact of the COVID-19 Pandemic on the Economy of Russian Regions

The COVID-19 pandemic has had a serious impact on the sustainability of the social, economic and environmental development of countries and regions. Differences in the structure of the economy of the subjects of Russia and the rate of spread of infection give rise to an assumption about the spatial unevenness of the economic consequences of the COVID-19 pandemic. The purpose of this work is to determine the degree of impact of COVID-19 on various types of regional economies, taking into account industry specifics. The article presents the theoretical base of the study based on foreign and domestic sources, considers the spread of coronavirus infection in the regions of the Russian Federation using the indicator “total number of cases of COVID-19 (per 1000 people)”, the dynamics of the unemployment rate at working age in the regions of Russia in 2018–2021, the dynamics of economic growth in the regions of the Russian Federation and the dynamics of the growth rate of GRP by sectors of the economy during the COVID-19 pandemic, specialization of the regions of the Russian Federation. Based on the results of the study, the regions of the Russian Federation were ranked according to the degree of influence of COVID-19 on their economic sphere: a) regions whose specialization is determined by natural and geographical factors (with the exception of tourism) experienced the least impact of the COVID-19 pandemic; b) regions whose economies are highly differentiated, large industrial and financial enterprises are located on their territory, the economic sphere of this group of regions has experienced a significant impact of the COVID-19 pandemic, but recovery has been rapid; c) regions in whose economy a number of pandemic risk factors have been concentrated; d) economic outsider regions in the Russian Federation. The conducted research complements the cycle of works in the field of the impact of epidemics on the economy of regions and countries. The results obtained can be used to develop and implement a risk management policy to mitigate the consequences of anti-epidemic measures in the regions of the Russian Federation.

High cadence cycling not high work rate, increases gait velocity post-exercise

ABSTRACT Gait velocity, or walking speed, has been referred to as the sixth vital sign, and research suggests that it is highly sensitive to change. Previous research has demonstrated the utility of cycling to improve gait parameters and in particular gait velocity in a variety of populations. However, it is unclear if the benefits from cycling to gait velocity stem from increased cadence, increased work rate, or the interaction between them. Therefore, the objective of the current research was to explicitly test the relationship between cycling work rate, cycling cadence, and gait velocity. 45 recreationally active young adults were randomly assigned to cycle at a normalised cadence and work rate, a higher cadence, or a higher work rate (CONTROL, FAST, HARD). All participants completed two ten-metre walk tests (10 MWT) pre- and post-cycling intervention. There was a significant interaction between group and time and post hoc comparisons showed that the FAST group walked significantly faster than the HARD group post-cycling. These results support the hypothesis that cycling at a cadence greater than the comfortable walking cadence, and not cycling at an increased work rate, increased gait velocity post-exercise for all members of our sample of healthy young adults.

Post-process updating of model parameters to approximate thermal errors of machine tools operating in different configurations

Machine tool (MT) thermal errors induced by external and internal heat sources (e.g. changing environment, friction and power losses in MT components) are an important element in machined workpiece inaccuracies. In the past few decades, indirect software compensation techniques have been used to address thermal errors on account of their economic and ecological aspects. Many slightly different approaches are described in the literature. If thermal error models are properly identified based on experiments with sufficiently varying input parameters, they usually work within similar calibration and verification conditions. As the sensory equipment of machines increases, models can be adapted to regions with higher thermo-mechanical system nonlinearity and inhomogeneity through the introduction of deformation feedback from direct measurements into model structures. However, adaptive functionalities require discrete interruptions of the MT's work cycle, which threaten the integrity of the machined surface and complicate the model structure and thus also implementation and industrial deployment possibilities. In this research, a novel approach of automatic post-process adaptation suitable for repetitive manufacturing, which takes advantage of transfer functions (TF), is proposed for thermal error reduction. The method respects basic heat transfer mechanisms in the MT structure by combining linear parametric models, requires a minimum of additional gauges, and feedback from direct measurements is obtained only during technological pauses in the production process. Post-process adaptation is solved retrospectively by updating model parameters using the heuristic method of genetic algorithms (GA). First, the approach was tuned on a case study of a heavy-duty milling machine with a horizontal headstock for a configuration with an exchangeable spindle head and a configuration with a change in the position of the headstock in the workspace, both of which were different from the initial model's calibration range. Subsequently, the developed approach was applied to repeated production on a medium-sized milling centre. Another goal of the paper is to emphasize the need for quality input information for modelling efforts and the industrial applicability of scientific results.

Experimental Investigation of a Pulsation Reactor via Optical Methods

Material treatment in pulsation reactors (PRs) offers the potential to synthesize powdery products with desirable properties, such as nano-sized particles and high specific surface areas, on an industrial scale. These exceptional material characteristics arise from specific process parameters within PRs, characterized by the periodically varying conditions and the resulting enhanced heat and mass transfer between the medium and the particulate material. Understanding flame behavior and the re-ignition mechanism is crucial to controlling the efficiency and stability of the pulse combustion process. In order to accomplish this objective, an investigation was conducted into flame behavior within the combustion chamber of a Helmholtz-type pulsation reactor. The study was focused on primarily analyzing the flame propagation process and examining flame velocity throughout the operational cycle of the reactor. Two optical methods—natural flame luminosity (NFL) and particle image velocimetry (PIV)—were applied in related experiments. An analysis of the NFL measurement data revealed a correlation between the intensity of light emitted by the pulsed flame and the air-fuel equivalence ratio (range from 0.89 to 2.08 in this study). It is observed that a lower air-fuel equivalence ratio leads to higher flame luminosity in the PR. In addition, in order to study the parameters related to system stability and energy transfer efficiency, this study also focuses on the local velocity field measurement method and an example of a fluid flow result in a combustion chamber by using a phase-locked PIV measurement system upgraded from a classic PIV system. The presented results herein contribute to the characterization of flame propagation within a pulsation reactor, as well as in pulsatile flows over one working cycle in a broader context, with flow velocity in the center of the combustion chamber ranging from 1.5 m/s to 5 m/s. Furthermore, this study offers insights into the applicable experimental methodologies for investigating the intricate interplay between flames and flows within combustion processes.

ОГНЕВЫЕ ИСПЫТАНИЯ МОБИЛЬНОЙ УНИВЕРСАЛЬНОЙ УСТАНОВКИ ПОЖАРОТУШЕНИЯ

To assess the effectiveness of a full-size mobile universal fire extinguishing system, fire tests of the developed layout of an experimental mobile universal fire extinguishing system were carried out, taking into account the requirements of national standards, which determined the choice of the operating pressure range and nozzle diameters. Numerical values of the duration of the supply, the length of the jet and the rate of discharge of fire extinguishing agent from the vessel of the layout of a mobile universal fire extinguishing system from the diameters of the nozzles with a change in pressure are obtained. The results showed that&#x0D; the duration of the supply and the length of the jet of fire extinguishing agent, regardless of the diameters of the nozzles, depend on the pressure, the flow rate and outflow rate of fire extinguishing agent depend on both the diameters of the nozzles and the pressure. The relationship between the parameters of the layout and its extinguishing capacity has been determined, which confirms the declared capabilities of its working cycle.

A Simulation Study of Noise Exposure in Sledge-Based Cable Yarding Operations

Ensuring the safety of forestry workers is a key challenge, particularly when working with partly mechanized harvesting systems. Cable yarding is typically used in steep terrain timber harvesting. For long-distance extraction, one of the few alternatives is to use sledge yarders, but these machines may expose workers to high doses of noise. The goal of this study was to model haulers’ exposure to noise in sledge-based cable yarding operations, based on a simulation approach that considered variable factors such as the yarding distance, lateral yarding distance, and average skyline height. Taken into consideration were 165 scenarios developed by examining the variation in yarding distance (500 to 1500 m, with a step of 100 m), lateral yarding distance (10 to 50 m, with a step of 10 m), and average skyline height above the ground (10, 15, and 20 m). The simulations assumed an 8-h working day with a break of 1 h. The models and statistics published by other studies were used to calculate the time consumption and number of work cycles completed within a working day. These data were used to compute the equivalent exposure to noise (LAeq) for each scenario, as well as for those work elements that were likely to expose the haulers to noise the most. The presented findings indicated that (i) the exposure to noise was higher than 100 dB(A), irrespective of variation in the considered factors; (ii) the trend in exposure was characterized by polynomials in relation to the extraction distance, and the magnitude of exposure was consistently affected by variation in the considered factors; and (iii) without hearing protection, the empty and loaded turns exposed workers to noise over the permissible limits. These findings strongly suggest the use of hearing protection when working in close proximity to sledge-based cable yarding operations. The methods proposed in this study in the form of simulation may help benchmark other forest operations.

Waste Heat Conversion to Power via Organic Rankine Cycle

several studies have been carried out on how to recover waste heat using Organic Rankine cycle. Each study applied different working conditions, power scale and cycle configuration, hence an assessment of working fluids is given for specific case. As a result, no single working fluid have been identified that would meet an entire heat source temperature levels. This motivated us to examine various substances for use as working fluids for subcritical ORC systems operating in the temperature range (543 - 633K). In this study, with a given finite thermal source, performance of working fluid candidates are evaluated and assessed using four criteria: thermal efficiency, exergy efficiency, total exergy destruction and net power output. Results of the study indicate that from a performance point of view, the linear alkanes such as nonane seem to be a suitable fluid in the temperature range (543-573K). Beyond aforementioned temperature range it appears that aromatic hydrocarbons such as toluene, ethylbenzene, P-xylene, O-xylene, propylbenzene preformed better. Under this condition, they represent comparably similar proposed screening criteria parameters and comparably high evaporating pressure, with only occasional slight differences between them.

Nightshift work and irregular menstrual cycle: 8-year follow-up cohort study.

Irregular menstruation is a major health problem among women, although its association with nightshift work remains controversial. To study the association between nightshift work and irregular menstrual cycle among female workers and investigate any differences according to sleep quality, working hours or obesity. This study included female workers who underwent health examinations from 2012 to 2019. Nightshift work, working hours, sleep quality and menstrual cycles were assessed using self-administered questionnaires. Irregular menstrual cycle was defined as self-reported irregular or ≥36 days. Adjusted odds ratios and 95% confidence intervals (CIs) were calculated by multivariable logistic regression; adjusted hazard ratios (95% CIs) for incident irregular menstrual cycle were calculated by Cox proportional hazard models with time-dependent analysis. The study participants were 87 147 in the cross-sectional study and 41 516 in the longitudinal study. After adjusting for all covariates in the cross-sectional analyses, the odds ratio for prevalent irregular menstrual cycle among female nightshift workers versus the reference was 1.26 (95% CI 1.2-1.33). In the cohort study, the adjusted hazard ratio for incident irregular menstrual cycle among nightshift workers was 1.95 (95% CI 1.61-2.35) in the period after 6 years. No significant differences were observed among subgroups stratified by sleep quality, working hours or obesity. Nightshift work is associated with an increased risk of both prevalent and incident irregular menstrual cycle in female workers without significant interactions by sleep quality, working hours or obesity.

The thermophysical properties of a promising composite adsorbent based on multi-wall carbon nanotubes for heat storage

AbstractThe use of energy from alternative energy sources as well as the use of waste heat are key elements of an efficient energetics. Adsorption heat storage is a technology that allows solving such problems. For the successful operation of an adsorption heat accumulator, it is necessary to analyze the thermophysical characteristics of the system under the conditions of the operating cycle: heat transfer coefficient adsorbent-metal (α2), overall (U) and global (UA) heat transfer coefficients of heat exchanger. Multi-walled carbon nanotube (MWCNT) composites are very promising for adsorption-based renewable energy storage and conversion technologies. In this work at the stage of heat release, α2 was measured by the large pressure jump (LPJ) method, at the stage of heat storage by large temperature jump method (LTJ), which made it possible to obtain thermophysical characteristics that corresponded to the implementation of the real working cycle as much as possible. The heat transfer coefficients for a pair of adsorbent LiCl/MWCNT—methanol are measured for the first time under the conditions of a daily heat storage cycle both at the sorption stage (α2 = 190 W/m2K) and at the desorption stage (α2 = 170 W/m2K).

Behavior of elastohydrodynamic lubricating film point contact problems in the unsteady state of reciprocating motion

Purpose In this study a numerical analysis of the elastohydrodynamic lubrication point contact problem in the unsteady state of reciprocating motion is presented. The effects of frequency, stroke length and load on film thickness and pressure variation during one operating cycle are discussed. The general tribological behavior of elastohydrodynamic lubrication during reciprocating motion is explained. Design/methodology/approach The system of equations of Reynolds, film thickness considering surface deformation and load balance equations are solved using the Newton-Raphson technique with the Gauss-Seidel iteration method. Numerical solutions were performed with a sinusoidal contact surface velocity to simulate reciprocating elastohydrodynamics. The methodology is validated using historical experimental measurements/observations and numerical predictions from other researchers. Findings The numerical results showed that the change in oil film during a stroke is controlled by both wedge and squeeze effects. When the surface velocity is zero at the stroke end, the squeeze effect is most noticeable. As the frequency increases, the general trend of central and minimum film thickness increases. With the same entraining speed but different stroke lengths, the properties of the oil film differ from one another, with an increase in stroke length leading to a reduction in film thickness. Finally, the numerical results showed that the overall film thickness decreases with increasing load. Originality/value General tribological behaviors of elastohydrodynamic lubricating point contact, represented by pressure and film thickness variations over time and profiles, are analyzed under reciprocating motion during one working cycle to show the effects of frequency, stroke length and applied load.

Artificial intelligence in healthcare: combining deep learning and Bayesian optimization to forecast COVID-19 confirmed cases.

Healthcare is a topic of significant concern within the academic and business sectors. The COVID-19 pandemic has had a considerable effect on the health of people worldwide. The rapid increase in cases adversely affects a nation's economy, public health, and residents' social and personal well-being. Improving the precision of COVID-19 infection forecasts can aid in making informed decisions regarding interventions, given the pandemic's harmful impact on numerous aspects of human life, such as health and the economy. This study aims to predict the number of confirmed COVID-19 cases in Saudi Arabia using Bayesian optimization (BOA) and deep learning (DL) methods. Two methods were assessed for their efficacy in predicting the occurrence of positive cases of COVID-19. The research employed data from confirmed COVID-19 cases in Saudi Arabia (SA), the United Kingdom (UK), and Tunisia (TU) from 2020 to 2021. The findings from the BOA model indicate that accurately predicting the number of COVID-19 positive cases is difficult due to the BOA projections needing to align with the assumptions. Thus, a DL approach was utilized to enhance the precision of COVID-19 positive case prediction in South Africa. The DQN model performed better than the BOA model when assessing RMSE and MAPE values. The model operates on a local server infrastructure, where the trained policy is transmitted solely to DQN. DQN formulated a reward function to amplify the efficiency of the DQN algorithm. By examining the rate of change and duration of sleep in the test data, this function can enhance the DQN model's training. Based on simulation findings, it can decrease the DQN work cycle by roughly 28% and diminish data overhead by more than 50% on average.

Dual phase change separator combining cooling and thermal shutdown functions for Li-ion battery with enhanced safety

The rapid growth of electric vehicles raises an unmet need to enhance high-temperature performance and safety of Li-ion battery (LIB). Herein, polyethylene glycol/polyvinylidene fluoride (PEG/PVDF) core @ polybutylene succinate (PBS) shell separator with cooling and thermal shutdown functions was fabricated using a one-step coaxial electrospinning method. The separator exhibited superior electrochemical performance even at room temperature due to good wettability and high porosity. When battery temperature rises as discharging, PEG with 50 °C melting point (m.p.) will melt to store heat temporarily. Thus, the separator with cooling function can effectively enhance ion conductivity to alleviate specific capacity drop and polarization voltage increase. As temperature decreases after battery discharging, the separator will release thermal energy to prepare for the next working cycle. When thermal runaway happens and raises temperate above 100 °C rapidly, the PBS shell will melt at 110 °C without skeleton thermal shrinkage. Separator pores can be blocked by the melted PBS and Li+ ions transfer can be inhibited in time to prevent disastrous consequence. Thus, dual phase change of the separator provides a novel and effective strategy for synergistic performance and safety enhancement of high temperature LIB.