Orthogonal Experiment Table Research Articles

Multiscale model of material removal for ultrasonic assisted polishing of cylindrical surfaces

Ultrasonic assisted polishing is an effective and precise method in engineering production that applies in finishing surface. A multiscale model was developed which is able to forecast the surface micromorphology and material removal rate. Process factors were considered include polishing force, grain diameter, ultrasonic amplitude and so on in this model at different scales. The impact of various process factors on surface roughness and material removal rate were analyzed by orthogonal experimental table. The perfect combination of process parameters was identified, and its effectiveness was verified through both simulations and experimental analysis, with an error rate below 9.43%. To provide a mechanism study of ultrasonic polishing of curved surfaces and optimization of process parameters by this theoretical model.

Diesel Engine Performance and Emission Parameters Optimization Using Taguchi and Response Surface Methodology

In present study, the ideal engine functioning condition for pollutants as well as functionality was determined using RSM. The L16 Orthogonal Array experiment table was designed using Minitab 16 software with Taguchi's design of experiments methodology with Three variables—fuel type, engine speed, and engine load, each of which was varied across four distinct levels. After a comprehensive model examination, the R2 and modified R2 values are close, indicating a low risk of including unimportant components. The model found that an engine load of 6.85 kgf, an engine speed of 2000 rpm, and the 20% OPB blended fuel (OPB20) would optimise BTE, EE, BSFC, and NO, HC, and CO emissions. The model's maximum desirability was 86.79%, indicating that the predicted optimum answers and experimental responses were similar. The utilisation of RSM optimisation in conjunction with OPB fuel has the potential to enhance engine performance and mitigate emissions.

A novel additive manufacturing strategy with high hydrogen production for ordered-porous stainless steel catalyst support

This paper proposes to improve hydrogen production performance of ordered-porous stainless steel by increasing its forming structure parameters. Firstly, selective laser melting additive manufacturing of ordered-porous stainless steel is carried out through designed orthogonal experiment table, to obtain its forming structure parameters under different manufacturing process parameters. Then, different forming structure parameters of ordered-porous stainless steel are converted into a comprehensive index by grey relation theory, which is grey relational degree (GRD). When powder thickness, scanning speed, scanning space and laser power are 30 μm, 800 mm/s, 90 μm and 60 W, respectively, the highest GRD of 0.930 is obtained, when those are 40 μm, 1200 mm/s, 70 μm and 60 W, respectively, the lowest GRD of 0.410 is gained. Finally, catalyst bonding strength and hydrogen production performance of the ordered-porous stainless steels with the above GRDs are verified. It is found that the ordered-porous stainless steel with the highest GRD has higher catalyst bonding strength and higher hydrogen production performance. When 12 mL/h injection rate of methanol–water solution and 250 ℃ reaction temperature are used, CH3OH conversion, H2 flowing rate and CO selectivity of the above ordered-porous stainless steel are 64.3%, 0.396 mol/h and 6.75%, respectively.

Modeling of creep-fatigue features of hydrogen storage bed and its parameter optimizing based on finite element method and orthogonal experimental design with artificial neural networks

Regarding the creep-fatigue behavior of hydrogen storage bed (HSB) structures under high-temperature loading and internal pressure loading under repeated hydrogen absorption and desorption process, the heat transfer characteristics and creep-fatigue life during a complete service process in HSB were calculated using Ansys Workbench and Ncode software, and the reliability of the life results calculated by finite element method were validated using ASME code. Based on orthogonal experimental design (OED) theory, an orthogonal experimental table with 4 factors and 5 levels was compiled for the four process parameters: diameter of cooling tube, thickness of cylinder wall, spacing between inner and outer layers, and heat transfer coefficient of condensate. Moreover, an optimization method based on OED coupled with BP ANNs was proposed to find the best process parameters. And the importance of each parameter was analyzed based on range analysis and analysis of variance (ANOVA) to divide the process parameters into rough optimized parameters and precise optimized parameters in this method. In order to identify the optimal process parameter combination of HSB, the maximum life and corresponding process parameter combinations were identified based on OED and the combined method, respectively. The maximum life identified by the combined method proposed in this work is increased by 10.23 % than that identified by OED, which shows the superiority of this combined method.

Optimization Design of Mining Tri-cone Bit Air Nozzle by CFD

Performance of the air nozzle of the mine tri-cone bit directly affects life of bit and rock breaking efficiency. The shape of air nozzle influences performance of mine tri-cone bit. It is necessary to optimize the shape of the air nozzle of tri-cone drill bits. The general specifications of gas mine tri-cone bit were analysed. Working condition and parameters of the air nozzle of the mine tri-cone bit were determined. A three-dimensional model of the air nozzle of the mine tri-cone bit was established. The characteristic geometry and range of air nozzle were determined. The performance index of air nozzle was proposed. An orthogonal experiment table of characteristic geometry of air nozzle was established. The ranking of influence weights of characteristic geometry was obtained. Key characteristic geometry which affects the performance of air nozzle was also obtained. This thesis work helps to improve the working performance of the gas nozzle of the three-cone bit. It can provide some reference ideas for the optimized design of the cone bit

Gradient-structured 1060 aluminum by air pressure-driven surface mechanical rolling treatment and its effects on the friction performance

Surface mechanical rolling treatment (SMRT) is well documented as a novel and promising surface self-nanocrystallization technology. An experiment platform of air pressure-driven surface mechanical rolling treatment was established innovatively, and the gradient-structured 1060 aluminum rod samples were accordingly fabricated by air pressure-driven SMRT. The air pressure, rolling pass and rotation speed of rod sample are the three parameters used for controlling the SMRT process. A three-factor and five-level orthogonal experiment table was designed to study the effects of the process parameters on the results of air pressure-driven SMRT of 1060 aluminum rod samples in terms of the surface roughness and in-depth microhardness. The experimental results show that the different combination of the three process parameters could obtain almost the same surface roughness or in-depth microhardness. Both the surface roughness and in-depth microhardness induced by air pressure-driven SMRT of 1060 aluminum rod samples are relatively more sensitive to the air pressure. Based on the microstructure observations, the grain refinement mechanism of 1060 aluminum induced by air pressure-driven SMRT was discussed in detail. The friction and wear experiments were further conducted to investigate the influences of the surface roughness and in-depth microhardness on the dry sliding wear behavior of the air pressure-driven SMRTed 1060 aluminum rod samples. In comparison to the reduction of surface roughness, the increase of the in-depth mircohardness has the more significant impact on the dry sliding wear behavior of the SMRTed 1060 aluminum rod samples.

Orthogonal design based pulse preheating strategy for cold lithium-ion batteries

The safety and availability of lithium-ion batteries are greatly affected by environmental temperature. Fast preheating of batteries is considered an effective technology for promoting the globalization of electric vehicles. This study establishes a coupled model of electro-thermal-aging to explore the advantages of pulse preheating methods in improving environmental adaptability and extending the service life of batteries. Firstly, the response of battery heating rate and capacity loss to the state of charge, positive pulse rate, pulse period, and the ratio of positive to negative pulse amplitude was analyzed. Additionally, the effects of various factors on the preheating effect of pulse current were explored. Secondly, appropriate factors and their levels were selected to construct an orthogonal experimental table. Then, the time and capacity loss rate were adopted as output response, multivariate analysis of variance and main effect analysis were performed on the factors and their levels in the orthogonal table. Moreover, the strategy of minimizing capacity loss and the shortest charging time for the pulse preheating method can be quickly determined based on the analysis results. Finally, the experimental results show that the developed preheating strategy achieves good results in terms of the heating effect and capacity retention rate.

Experimental and numerical simulation verification of depositional characteristics of NH4Cl particles under variable conditions

ABSTRACT The primary cause of U-tube heat exchanger leakage and perforation is attributed to the deposition and corrosion of NH4Cl within the condensing pipeline located at the summit of the crude oil distillation tower. This paper aims to investigate the deposition law of NH4Cl in U-shaped tubes under variable operating conditions and the impact of diverse factors on the deposition features of NH4Cl. To achieve this objective, the study establishes appropriate experimental equipment, designs a 4-factor and 4-level orthogonal experimental table, and manipulates the variables of particle incidence velocity (v), relative humidity (RH), particle size (d), and temperature (T). The experimental results of each group are recorded and analyzed. The observed experimental data reveals that under the operational parameters of Group H (v: 7 m/s, RH: 50%, d: 0.7 mm, T: 140°C), particle accumulation peaks at the elbow outlet, resulting in a substantial volume ratio of 17.14%. Conversely, Group M (v: 10 m/s, RH: 1%, d: 0.1 mm, T: 140°C) demonstrated the minimal particle deposition in the angular sector between 30° − 60° of the elbow, yielding a minimal volume ratio of 0.22%. Further scrutiny suggests that environmental humidity and incident flow velocities significantly influence particle deposition, whilst ambient temperature and particle size exert less substantial effects. A multivariate linear deposition equation between NH4Cl deposition and v, RH, d, T was derived through linear regression, yielding an Rc2 of 0.913, indicating a high level of concordance. A mathematical model was constructed, incorporating computational fluid dynamics (CFD), to simulate and analyze the flow characteristics of ammonium chloride particles in U-shaped tube bundles, which was subsequently validated with the experimental results obtained, the comparison results showed a good degree of coincidence, with an error of 4.41%.

Preparation Scheme Optimization of Thermosetting Polyurethane Modified Asphalt.

To solve the issue of the poor temperature stability of conventional modified asphalt, polyurethane (PU) was used as a modifier with its corresponding curing agent (CA) to prepare thermosetting PU asphalt. First, the modifying effects of the different types of PU modifiers were evaluated, and the optimal PU modifier was then selected. Second, a three-factor and three-level L9 (33) orthogonal experiment table was designed based on the preparation technology, PU dosage, and CA dosage to prepare the thermosetting PU asphalt and asphalt mixture. Further, the effect of PU dosage, CA dosage, and preparation technology on the 3d, 5d, and 7d splitting tensile strength, freeze-thaw splitting strength, and tensile strength ratio (TSR) of the PU asphalt mixture was analyzed, and a PU-modified asphalt preparation plan was recommended. Finally, a tension test was conducted on the PU-modified asphalt and a split tensile test was performed on the PU asphalt mixture to analyze their mechanical properties. The results show that the content of PU has a significant effect on the splitting tensile strength of PU asphalt mixtures. When the content of the PU modifier is 56.64% and the content of CA is 3.58%, the performance of the PU-modified asphalt and mixture is better when prepared by the prefabricated method. The PU-modified asphalt and mixture have high strength and plastic deformation ability. The modified asphalt mixture has excellent tensile performance, low-temperature performance, and water stability, which meets the requirements of epoxy asphalt and the mixture standards.

Optimizing Structural Parameters of PEMFC Based on Taguchi Method

Proton exchange membrane fuel cell (PEMFC) has become one of the new energy vehicle powertrains due to its special advantages, such as no pollution to the environment, high energy efficiency and power density. In order to improve the performance, a three-dimensional simulation model of the actual PEMFC is constructed. Combined with the mathematical models such as the electrochemical model and current conservation model, the model is calibrated by experiments. When the working voltage is 0.64 V, the error of the simulation results is 0.73%, compared with the experimental data. Then, the Taguchi method is used to design a multi-factor and multi-level orthogonal experimental scheme of PEMFC. Based on the orthogonal experimental table, the effects of different anode wave channel distortion, gas diffusion layer thickness and gas diffusion layer porosity on the current density are studied with a simulation experiment. The influence of the above factors on the orthogonal experiment results is analyzed by the signal-to-noise ratio. The regression equation is obtained by calculating the orthogonal experimental data. The t-test results are greater than 3.49, which indicates that each independent variable in the regression equation is important. R2 test is 0.915, and the F test is 53.508, indicating that the regression equation is significant and the optimal and worst structural parameter combinations are predicted. The current density reaches 14,190.18 A/m2 under the optimal structure combination, which is 6.14% higher than the calibrated model. Single factor experiments are carried out on these three different structural parameters to verify the effectiveness of the Taguchi method, and the best combination of structural parameters is obtained.

Rhenium-molybdenum separation in an alkaline leaching solution of a waste superalloy by N263 extraction

The recovery of rhenium from waste superalloys has always been a research focus. This study focuses on the performance of extraction of rhenium and its separation with molybdenum in alkali leaching solution of waste superalloy by methyl trioctylammonium chloride (N263). Minitab 17 Statistical Software (Trial version, Techmax, USA) was used to create a four-factor (N263 concentration, sec-octyl alcohols concentration, extraction time and organic to aqueous ratio (O/A ratio)) two-level orthogonal experiment table. According to the orthogonal experiment results of rhenium extraction and rhenium molybdenum separation coefficient, rhenium extraction model, rhenium molybdenum separation coefficient model and the corresponding regression equation were established. The rhenium extraction performance of N263 was investigated by the rhenium equilibrium curve and NaSCN concentration. It was found that the N263 concentration was the main factor affecting rhenium extraction, and the regression equation of rhenium extraction was Re extraction/% = 0.672 + 9.880 [N263]. Moreover, N263 concentration and O/A ratio are the main factors affecting rhenium molybdenum separation coefficient. The regression equation of rhenium molybdenum separation coefficient is βRe/Mo = 37.5 + 116.88* [N263] −24.3 *(O/A ratio) −20.62 [N263]*(O/A ratio). At the same concentration of the rhenium stripping agent, the rhenium stripping efficiency is perchloric acid > nitric acid > sodium thiocyanate. However, the strong oxidability of perchloric acid and nitric acid destroys the organic phase, making the organic phase produce visible destruction. The rhenium stripping was about 75.8 % with 40 times the theoretical amount of sodium thiocyanate. The results showed that Re was easy to be extracted in the alkali solution, but it was not easy to be stripped from the loaded N263 phase.

Multi-Objective Optimization of an Axial Flux Permanent Magnet Brushless DC Motor with Arc-Shaped Magnets

To get a better electromagnetic performance of an axial flux permanent magnet brushless DC motor (AFPMBLDC), an AFPMBLDC with arc-shaped magnets and its multi-objective optimization design are researched. Firstly, the main design parameters of the AFPMBLDC are proposed, and the initial designs are carried out according to the given requirements. Furthermore, the pole arc coefficient, permanent magnet thickness, permanent magnet arc radius, and air-gap length are selected as optimization factors. Then, an orthogonal experiment table is established, in which the flux density, no-load back EMF, harmonic distortion rate, and output torque ripple are selected as optimization targets. The Taguchi optimization method is adopted to optimize the performance indexes and the optimal parameters are obtained. Finally, the optimized model is constructed, and some simulations are carried out to verify the optimal design. The research results have shown that the air-gap flux density of the optimized AFPMBLDC is reduced to 31.8%, the total harmonic distortion rate of no-load back EMF is less than 7.5%, and the torque ripple is reduced to 4.3%.

Evaluation of different factors on metal leaching from nickel tailings using generalized additive model (GAM)

Compared with sulfide tailings, the oxidation and transformation of certain substances in oxidized tailings into more soluble forms may affect the bioaccumulation and biomagnification properties and enhance the risk of toxic effects in the ecosystem. This study aimed to apply the generalized additive model (GAM) to evaluate factors affecting heavy metal leaching from nickel (Ni) tailings. We created an orthogonal experiment table (L18(37)) to evenly distribute the different combinations of factor values. The Ni tailings were immersed in solutions with different combinations of factor values for 16 d, and samples were taken on days 1, 2, 4, 7, 11, and 16 to measure the pH and heavy metal concentration of the leachate. The GAM was used to fit the concentration of heavy metals of the leachate and the initial factors of the leaching solution. The results showed that the pH and Cr concentration of the leachate increased with time and stabilized after 1 d (pH of approximately 7), while the Mn, Ni, and Tl concentrations gradually decreased and stabilized after peaking on the first day. An analysis of the GAM results showed that the Cr concentration was highly sensitive to the solid-liquid ratio (F = 127.8) and tailing particle size (F = 10.7). The Cr concentration of the leachate was significantly higher when exposed to a high solid-liquid ratio or a fine particle size, whereas the Mn, Ni, and Tl concentrations were highly sensitive to the KCl concentration and solid-liquid ratio (F = 77.4, 146.9, and 315.9 respectively). The GAM identified interactions between key factors, which have complex and strong effects on the leaching of tailings and the migration of heavy metals, either promotional or antagonistic. The prediction of the minimum Cr leaching concentration shows that GAM can be used to determine the conditions associated with minimum leaching concentrations of heavy metals and to effectively predict the metal concentrations of leachate. As such, the results of this study can be applied to the management of nickel tailings.

Research on the Effects of Machining Parameters on the Surface Location Error for a Milling Process

The surface location error is an inevitable phenomenon which is caused by the forced vibration under a stable machining process. The surface location error (SLE) is dependent on the machining parameters. Therefore, this paper proposes a method to study the effect of each machining parameter on the surface location error. An algorithm based on the cutting force dynamic model is proposed to predict the SLE in frequency domain. And then a case study is performed on the milling process of a real vertical machining center. The variation ranges of the spindle speed, axial cutting depth, radial cutting depth and feed rate per tooth are first determined. Eight specific values of each machining parameter is selected, and an orthogonal experiment table is established to arrange the schemes to predict the corresponding SLEs. Then the range analysis is used to analyse the values of the machining parameters and the obtained SLEs. Results show that the spindle speed is the most dominant factor affecting the SLE and an optimal machining parameters combination related to a minimum SLE is determined based on the optimal level of each machining parameter.

Thermosetting Coupling Analysis and Parameter Optimization of the Plastic Lining Pump Structure

In order to obtain the optimum structure of the lining pump under the condition of fluid thermosetting coupling, according to the given design parameters, the structural parameters of the pump were calculated, the three-dimensional geometric model was established, and the flow field analysis was carried out by CFD; the inlet angle βb1, outlet angle βb2, wrap angle φ, inlet diameter D1, and outlet diameter D2 of the impeller were selected as the five factors to design orthogonal experiment, and the results were analyzed by range analysis; then, the efficiency and cavitation allowance were obtained as combined parameters under the evaluation index. The displacement deformation and stress distribution under the condition of the coupling field were obtained by the fluid-solid coupling analysis, and the orthogonal experimental table of the impeller structure of the lining plastic pump was established, and then the orthogonal experimental results are analyzed to obtain the influence of each structural parameter under the condition of each evaluation index and the optimum combination parameters. The influence situation and the best combination parameters under the condition of evaluation index, taking the minimum displacement deformation and minimum stress of impeller as the reference index, and the optimum combination parameters under the condition of minimum displacement and stress were as follows: the inlet diameter D1 was 76 mm, the outlet diameter D2 was 252 mm, the inlet angle was 26°, the outlet angle was 24°, and the wrap angle was 115°. Finally, the 3D printing technology was used to print out the physical model to the hydraulic performance experiment verification.

Selection of optimal combinations of inputs in a partial least squares model for prediction of soil organic matter

Partial least squares model is widely used in estimation of soil physical and chemical parameters such as soil organic matter and moisture content, due to its advantages in dealing with collinearity of variables like hyperspectral reflectance. However, it is hard to determine optimal combination of partial least squares model input for soil organic matter prediction since there are lots of possibilities such as, different mathematical transformation of spectral reflectance, wavelength ranges, and spectral resolution. Laboratory hyperspectral reflectance of soils in Songnen plain were analyzed in this study, and the orthogonal experimental design method for deriving optimal combination of input variables for soil organic matter prediction models was introduced. For intercalating orthogonal experimental design table, five different levels which commonly used by researchers were assigned to factors. Results show that the optimal combination input for single black soil is using the derivative logarithmic reciprocal reflectance in the wavelength range selected by multiple stepwise regression at a spectral resolution of 5 nm (R2= 0.95, RMSE = 0.21, and RPD = 4.49), and different soils is using continuum removed in the wavelength range selected by MSR at a spectral resolution of 5 nm (R2 = 0.77, RMSE = 0.74, and RPD = 2.08). With optimal combination input, the partial least squares model prediction ability was evaluated as excellent for single black soil, possible for different soils. This study illustrates the orthogonal experimental design method can be an effective way to identify the optimal input variables of a partial least squares model for soil organic matter prediction, and multiple stepwise regression can be a preprocessing step to reduce hyperspectral data redundancy before using partial least squares to predict soil organic matter. Overall, this study provides a new approach for determining optimal input of partial least squares predicting model.

Water Flow Regulation and Scheme Optimization in the Haihe River

Abstract To improve water quality in the Haihe River, 6 cycle routes and 16 water diversion schemes were simulated, and their influence on water quality was analyzed. First, a one-dimensional hydrodynamic and water quality model of the Haihe River was established. Then, according to an orthogonal experiment, 16 cycle schemes were proposed, and an orthogonal experimental table, including 3 factors and 4 levels, was used to optimize the 16 schemes. Average pollutant concentration from Sanchakou to the Erdao Sluice served as the index for orthogonal experiments. Index values were obtained from the model and the influence of three factors on chemical oxygen demand, total nitrogen, total phosphorus, and nitrogen ammonia was evaluated by range analysis. In addition, optimal schemes to reduce pollutants in each route were also obtained. After comparing the simulated results of the optimal schemes in each route, an optimal route was obtained. A combination of the one-dimensional hydrodynamic and water quality mod...

Milling Parameters Optimization of MgCa0.8 Alloy Based on Orthogonal Experiment

To study the influence of cutting parameters on the surface quality of the MgCa0.8 alloy in milling with the coated carbide tool, orthogonal experiment table of three factors and four levels was designed, which considered the spindle speed, depth of cut and feed per tooth as the main factors. The optimal level and the optimal combination of cutting parameters were obtained by range analysis method. Finally, Variance Analysis Method and F-test were used to analyze the significance of the cutting parameters on both the surface roughness and the cutting force Fx. We verified that the change of the feed per tooth has the relatively most significant effect on the surface roughness of the part and the depth of cut has the relatively most important effect on the cutting force Fx.

The optimal combination of mechanical ventilator parameters under general anesthesia in obese patients undergoing laparoscopic surgery

ObjectivePulmonary dysfunction after laparoscopic surgery is commonly seen in the high-risk group of obese patients. To reduce or avoid this complication caused by an improper combination of mechanical ventilation parameters, we conducted the following trial of 3 factors with 3 levels of mechanical ventilation, aimed to obtain the low airway pressure with good ventilator effects. MethodsPatients were randomly allocated as a sample of cases according to the “30≤weight/height2<40” obesity index. Anesthesia machine was checked on the most fundamental respiratory frequency (f), tidal volume (VT), and respiratory ratio (I:E) as the 3 factors of A, B, and C, with 3 levels of f=15, 12, 9 (beats per minute), VT=8, 10, 12 (mL/kg), and I:E=1:2.5, 1:2.0, 1:1.5. By using L9 (34) K=3 repeat, the orthogonal experimental design and analysis table for statistics, testing, and analysis of the factors that affect the respiratory and change at the end of the level of carbon dioxide (PETCO2), peak airway pressure (PIP), mean airway pressure (Pmean), and the end of endogenous airway pressure (PEEPi) are of statistical significance. SPSS 13.0 analysis of variance was used for statistically significant test, with P<.05 and P<.01 as statistically significant differences. ResultsIn this study, a total of 27 cases of laparoscopic surgery were allocated in 9 experimental groups under general anesthesia. Patients' vital signs are stable; SPO2 is 100%. There are different combinations among 3 factors and 3 levels of parameters: (1) the impact on the PETCO2, respiratory frequency (f), and/or VT, choose either level, P<.01 means statistically significant, respiratory ratio (I:E) of either selection, P>.05, not statistically significant; (2) the impact of PIP: respiratory frequency (f) change, P<.05, significant difference, VT and I:E changes, P<.01 means statistically significant; (3) the impact of airway pressure on average (Pmean): 3 factors and 3 levels of selected respiratory parameters, P<.01 means statistically significant. ConclusionThe best combination of respiratory parameters is A3B1C2, that is, f=9beats per minute, VT=8mL/kg, and I:E=1:2.0. That is, neither small tidal volume and faster frequency nor slow frequency large tidal volume is a good choice. To let obese patients under general anesthesia can obtain a lung protective effect of low airway pressure with good ventilation; it is noteworthy that (1) I:E of airway pressure (PIP, Pmean) is the important impact factor for the protection of the lung and (2) I:E of airway pressure (PIP, Pmean) is the factor with opposite properties.

Hybrid Biological Fiber-Reinforced Resin-Based Friction Materials Friction and Wear Performance Test

Friction material is essential for automotive braking system. Based on previous study of existing friction material problems, hybrid biological fiber-reinforced resin-based friction materials (HBRMs, from the reinforced fiber component of resin-based friction materials) were explored in this study. Bamboo fiber, jute fiber and wool fiber (all have length of 3-5 mm) were processed to make three types of HBRMs and considered as three factors of biological reinforced fiber in test using orthogonal experimental design. Each factor had three levels of 1%, 2% and 3% fiber mass fraction while the ratio of other raw materials remains unchanged. According to the orthogonal experimental design table, nine formulations (denoted as M1-M9) were determined to test the HBRMs. For comparison, non-bio-fiber reinforced friction material (NBM) was added in the test. The properties of the HBRMs tested included Rockwell hardness, impact strength and density. The friction and wear performance of the braking materials was examined by a speed friction tester. The results show that the friction coefficient of the HBRMs was slightly higher than that of the NBM, indicating biological fibers affected the friction coefficient. The friction coefficient of the HBRMs decreased firstly with the increase of temperature and had the lowest value when the temperature reached 300°C, and it increased then as temperature increased. During recovery process, the friction coefficient of the HBRMs firstly increased with the decrease of temperature and then decreased greatly when the temperature dropped to 100°C. The wear rates of the HBRMs increased with the increase of temperature and reached maximum value when temperature reached 200°C, then it decreased with the increase of temperature. The results of fuzzy comprehensive evaluation analysis on the friction coefficient and wear rate show that the best comprehensive properties were presented when the mass fraction of bamboo, jute and wool fiber were 3%, 3% and 1%，respectively.