Accurate Estimation Method Research Articles

Lumped Radial Force Characteristics Reconstruction for Switched Reluctance Machines Through Scaling Flux-Linkage Characteristics

This article presents a simple and practical method to estimate the lumped radial force characteristics for the switched reluctance machines (SRMs). First, the relationship between the square root of the lumped radial force and the flux linkage is discussed and analyzed. With the geometry data of the studied SRM, the abovementioned relationship under nominal air-gap length and nominal material magnetic property conditions can be obtained through the finite-element analysis (FEA) software. As the radial flux density dominates the magnitude of the radial force and it concentrates on the overlapping area, the abovementioned relationship is analyzed to be roughly held when the air-gap length and/or material magnetic property vary. Based on this relationship obtained from the FEA and the actual measured flux-linkage characteristics, the lumped radial force can be easily reconstructed for the actual SRMs regardless of the possible air-gap length variation and material magnetic property deviation during the manufacturing process. Simulation results on the 8/6 SRM and 12/8 SRM verify that the proposed method provides good radial force estimation results when the air-gap length is reduced or increased up to 50%. Superior estimation results are also observed on the condition that the magnetic <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${B}$ </tex-math></inline-formula> – <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${H}$ </tex-math></inline-formula> curve is linearly varied by ±25%. The accurate and simple radial force estimation method proposed in this article provides a solid basis for the radial-force-shaping-based advanced control methods to suppress the acoustic noise.

Lithium-Ion Batteries Long Horizon Health Prognostic Using Machine Learning

Long horizon state of health (SOH) monitoring and remaining useful life (RUL) prediction are of industrial value in prognostic and health management (PHM) of lithium-ion batteries (LIBs) to ensure their reliable functionality by early detection. Machine Learning, as a data-driven health diagnostic technique, has been widely utilized in solitary and hybrid structures. However, an accurate SOH estimation and RUL prediction method with less computational burden are highly desirable for the online state prediction in an electric vehicle application. This paper evaluates nonlinear autoregressive with external input (NARX) recurrent neural network (RNN) and time delay neural network (TDNN) in their prediction precision using the NASA dataset. The superior method, NARXRNN, is employed for two different datasets to estimate the battery's SOH and predict its RUL on a broad horizon. The results reveal the outstanding performance by presenting the root mean square error within 3% and mean absolute error within 2% for unseen data. Therefore, this method is capable to accurately predict the SOH of LIBS from historical data at low computational complexity. It is a promising model for long horizon SOH and RUL prediction and practical for online applications.

State-of-Health Estimation for LiFePO4 Battery System on Real-World Electric Vehicles Considering Aging Stage

Comprehensive and accurate estimation methods of the state of health (SOH) of battery systems play a significant role in online monitoring for the safe and reliable operation of electric vehicles (EVs). Most existing estimation techniques are established on top of data from well-controlled experimental environments and tend to focus on a single health feature, thus not practical for real-world EVs’ SOH monitoring throughout the life cycle. To address this problem, based on real-world EV operation data, a novel SOH estimation model is presented for LiFePO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sub> battery systems in EVs with consideration of degradation mechanisms. The ohmic resistance and the peak value of the incremental capacity (IC) curve are extracted from a large number of electric buses as health features. The influence of temperature on the ohmic resistance is eliminated by exponential fitting, which transforms ohmic resistance into the relative change rate of ohmic resistance. With joint considerations of the two health features and the mechanism of battery aging, three stages of SOH degradation can be quantitively described. The test results show that the proposed model is able to track SOH degradation from 0 to over 300 000 km and reflect the SOH of the battery more comprehensively in the early and late life cycles of the battery compared with single-health-feature methods.

Implementation of QbD Approach to the Analytical Method Development and Validation for the Estimation of Metformin Hydrochloride in Tablet Dosage Forms by HPLC.

The current studies entail quality by design (QbD)-enabled development of a simple, rapid, precise, accurate, and cost-effective high-performance liquid chromatographic method for estimation of metformin hydrochloride (M-HCl). Design of experiments (DoE) was applied for multivariate optimization of the experimental conditions of the HPLC method. Risk assessment was performed to identify the critical method parameters (CMPs) using Ishikawa diagram. The factor screening studies were performed using a two-factor three-levels design. Two independent factors, buffer pH and mobile phase composition, were used to design mathematical models. Central composite design (CCD) was used to study the response surface methodology and to study in depth the effects of these independent factors, thus evaluating the critical analytical attributes (CAAs), namely, retention time, peak area, and symmetry factor as the parameters of method robustness. Desirability function was used to simultaneously optimize the CAAs. The optimized and predicted data from contour diagram consisted of 0.02 M acetate buffer pH = 3/methanol in a ratio of 70/30 (v/v) as the mobile phase with a flow rate 1 mL/min. The separation was made on a Thermoscientific ODS HypersylTM chromatographic column (250 × 4.6 mm, 5 μm) with oven temperature 35 °C and UV detection at 235 nm. The optimized assay conditions were validated according to ICH guidelines. Hence, the results clearly showed that QbD approach could be successfully applied to optimize HPLC method for estimation of M-HCl. The method was applied both for the evaluation of M-HCl content in tablets, and for in vitro dissolution studies of M-HCl from conventional and prolonged-release tablets.

Accuracy of Iranian Cameriere and Willems methods for estimating dental age in a population of Iranian children

Age estimation methods based on dental radiographs are of the most accurate and popular methods for age estimation. The accuracy of these methods might vary between different ethnic groups. Therefore, the present study was performed in order to evaluate and update the Cameriere dental age estimation method in a population of Iranian children and compare it with the Willems dental age estimation method. A retrospective cross-sectional study was performed, using dental records and digital dental panoramic radiographs of 110 six- to 12-year-old patients (55 girls and 55 boys). In order to assess the accuracy of both methods, the difference between the estimated dental age and the Chronological age was calculated and compared. Results of the present study showed Willems method overestimated the age and the updated Iranian Cameriere method underestimated the age, but the over/underestimations were not significant, except for the boys in Willems group. Both Willems dental age estimation (WDA) and Iranian Cameriere dental age estimation (ICDA) methods were applicable in the selected population of Iranian children, although the WDA estimations were less accurate, especially for boys.

Development and Validation of New Analytical Method for Estimation of Anthelmintic in Tablet Dosage Form

A rapid, sensitive and accurate method for Estimation of Anti- Histamine in Tablet Dosage Form by RP-HPLC. Mobile phase was Methanol: 0.1% Ortho phosphoric acid (80:20% v/v). Flow rate was 0.9 ml/min. The detection Wavelength was 227 nm. The injection volume was 20-µl. The proposed method was validated for selectivity, precision, linearity, and accuracy. All validation parameters were within the acceptable range. Linearity studies for Levamisole was performed (10-60µg/ml). The %RSD for accuracy found to be less than2%. Assay was found to be 99.17 to 101.65 respectively The range of 10-60µg /ml was selected for the linearity of a standard Levamisole. The 80%, 100% and 120% levels of recovery study were selected to perform the recovery study. Linearity studies for Levamisole was performed on (10-60µg /ml).

A Comparison of Actual versus Estimated Weights among Filipino Children Using the Original and Updated Advanced Paediatric Life Support (APLS) Formulae, Mercy Method and Broselow Tape: A Prospective Study

Introduction. In resuscitating children, actual weight should be obtained before intervention. However, this is not always possible in the emergency setting. Identifying a simple, accurate, and precise method of weight estimation is essential in the delivery of optimal care for Filipino children seen at the emergency department.&#x0D; Objectives. To evaluate and compare the accuracy and precision of different weight estimation methods in Filipino children.&#x0D; Methods. A cross-sectional, single-center study was conducted among patients aged &gt;28 days-12 years seen at the Philippine General Hospital Emergency Room. The traditional and updated Advanced Pediatric Life Support (APLS), Broselow tape, and Mercy Method were used for weight estimation. Bland Altman analysis was performed to see the mean difference and limits of agreement between actual and estimated weights of the children.&#x0D; Results. Broselow tape gave the closest average weight estimate, overestimating it by 0.7 kg, followed by Mercy method at 0.955 kg higher than actual. Traditional APLS yielded 1.565 kg and the Updated APLS 3.299 kg. Mercy Method had the narrowest limit of agreement.&#x0D; Conclusion. Among the four weight estimation methods, Broselow tape is the most accurate while the Mercy method is the most precise. Traditional APLS performed better than the updated APLS. Length-based methods and anthropometric surrogates proved to be more reliable than age-based formulae.

Development and Validation of New Analytical Method for Estimation of Anti-histamine in Tablet Dosage Form

A rapid, sensitive and accurate method for Estimation of Anti- Histamine in Tablet Dosage Form by RP-HPLC. Mobile phase was Methanol: 0.1%. Ortho phosphoric acid (80:20% v/v). Flow rate was 0.9ml/min. The detection Wavelength was 227nm. The injection volume was 20µl.The proposed method was validated for selectivity, precision, linearity, and accuracy. All validation parameters were within the acceptable range. Linearity studies for Rupatadine Fumarate were performed (10-60µg/ml). The %RSD for accuracy found to be less than 2%. Assay was found to be 99.17 to 101.65 respectively. The range of 10-60µg /ml was selected for the linearity of a standard Rupatadine Fumarate. The 80%, 100% and 120% levels of recovery study were selected to perform the recovery study. Linearity studies for Rupatadine Fumarate was performed on (10-60µg/ml).

Green Area Index and Soil Moisture Retrieval in Maize Fields Using Multi-Polarized C- and L-Band SAR Data and the Water Cloud Model

The green area index (GAI) and the soil moisture under the canopy are two key variables for agricultural monitoring. The current most accurate GAI estimation methods exploit optical data and are rendered ineffective in the case of frequent cloud cover. Synthetic aperture radar (SAR) measurements could allow the remote estimation of both variables at the parcel level, on a large scale and regardless of clouds. In this study, several methods were implemented and tested for the simultaneous estimation of both variables using the water cloud model (WCM) and dual-polarized radar backscatter measurements. The methods were tested on the BELSAR-Campaign data set consisting of in-situ measurements of bio-geophysical variables of vegetation and soil in maize fields combined with multi-polarized C- and L-band SAR data from Sentinel-1 and BELSAR. Accurate GAI estimates were obtained using a random forest regressor for the inversion of a pair of WCMs calibrated using cross and vertical co-polarized SAR data in L- and C-band, with correlation coefficients of 0.79 and 0.65 and RMSEs of 0.77 m2 m−2 and 0.98 m2 m−2, respectively, between estimates and in-situ measurements. The WCM, however, proved inadequate for soil moisture monitoring in the conditions of the campaign. These promising results indicate that GAI retrieval in maize crops using only dual-polarized radar data could successfully substitute for estimates derived from optical data.

A data-model fusion method for online state of power estimation of lithium-ion batteries at high discharge rate in electric vehicles

This paper proposes a novel data-model fusion method (DMFM) for online state of power (SOP) estimation of lithium-ion batteries at high discharge rates in electric vehicles. First, battery polarisation characteristics responding for high discharge rates are experimentally investigated through a series of decremental pulse tests. Battery polarisation voltage is observed with diverse growing patterns over a whole battery operation range, and its underlying correlations with state of charge (SOC), discharge rate and pulse runtime are recognised. Second, a feed-forward neural network (FFNN) with SOC, discharge rate and pulse runtime as inputs, is constructed to characterise battery polarisation voltage through modelling the current excited polarisation resistance. Third, a DMFM is proposed to combine the data-driven method and equivalent-circuit model based method for accurate online SOP estimation in a lengthy prediction window ranging from 30 s to 120 s. Moreover, an unscented Kalman filter is devised to filter the estimation outcomes of the DMFM for noise suppression. The experimental results validate the effectiveness of the constructed FFNN in reproducing the nonlinearity of battery polarisation characteristics at high discharge rates and show the significant improvement in SOP estimation accuracy. • A novel data-model fusion method is proposed for online SOP estimation. • Battery polarisation characteristics at high discharge rates are investigated. • A feed-forward neural network is constructed for battery polarisation modelling. • Experimental validations are conducted under the dynamic load profile.

FEM-Bayesian Kriging method for deformation field estimation of earth dams with limited monitoring data

The health monitoring and operation behavior assessment of earth dams are research focuses in geotechnical engineering. Due to the limited monitoring data and the uncertainty of material properties, existing monitoring data-based interpolation methods and mechanism-based finite element method (FEM) can not accurately estimate the dam deformation field. Therefore, studying an accurate estimation method of the deformation field is important to guarantee the serviceability of earth dams. In this paper, a FEM-Bayesian kriging (FBK) method is proposed, in which the FEM is introduced into the Bayesian kriging framework as the source of soft data, taking the FEM results as a trend surface of the deformation field, the spatial distribution of the random residual is determined by the exact monitoring data, thereby the FEM results are corrected. In this method, data-rich but low-precision FEM results and limited but high-precision monitoring data are coupled to approach the real deformation field. A numerical experiment is designed to verify the accuracy of the proposed method, and the estimation error of the FBK is reduced by about 80% compared with traditional methods. The case study of an actual earth dam also shows that the proposed method can effectively characterize the deformation behavior of earth dams.

RP-HPLC Method development and validation for simultaneous estimation of montelukast and ebastine in pharmaceutical dosage form

Combination therapy of Montelukast (MNK) and Ebastine (EBA) provide anti-asthmatic effector the maintain treatment of asthma and relieve symptoms of allergies. The objective of this study is development of a new simple, accurate, sensitive, and reproducible RP-HPLC method for simultaneous estimation of MNK and EBA in pharmaceutical formulation (tablet) using Ofloxacin (OFL) as an internal standard and validate the same as per ICH guidelines. The chromatogram separation was achieved on Qualisil-5 BDS C8 column (250 mm × 4.6 mm, 5µm) column with mobile phase acetonitrile: water (pH 2.8 with TFA) in the composition of 84:16 v/v at a flow rate of 1 mL/min using PDA detector at 254 nm at ambient column temperature, keeping the injection volume 20 μL. The retention time of OFL, MNK, and EBA was observed to be 2.107 min, 2.517 min, and 3.819 min, respectively. All the criteria for the validation (linearity, accuracy, precision, and robustness) were observed to be within the acceptation range. The calibration plots were obtained between 5-60 µg/mL for MNK and 5-60 µg/mL for EBA with r2 values of 0.999 in each case. The recovery of MNK and EBA was found to be 98.99% and 99.40%, respectively with a % RSD of &lt;2. This RP-HPLC method was found to be rapid, specific, precise, and accurate and can be used for the routine analysis of MNK and EBA in bulk as well as in tablet dosage form. The separation was complete with a shorter analysis time along with well good resolved peak.

Development and Validation of Stability Indicating RP-HPLC Method for Estimation of Levamisole HCl in Bulk and Tablet Dosage Form

A rapid, sensitive and accurate method for Estimation of Anti- Histamine in Tablet Dosage Form by RP-HPLC. Mobile phase was Methanol: 0.1% Ortho phosphoric acid (80:20% v/v). Flow rate was 0.9ml/min. The detection Wavelength was 227nm. The injection volume was 20-µl. The proposed method was validated for selectivity, precision, linearity, and accuracy. All validation parameters were within the acceptable range. Linearity studies for Levamisole was performed (10-60µg/ml). The %RSD for accuracy found to be less than2%. Assay was found to be 99.17 to 101.65 respectively The range of 10-60µg /ml was selected for the linearity of a standard Levamisole. The 80%, 100% and 120% levels of recovery study were selected to perform the recovery study. Linearity studies for Levamisole was performed on (10-60µg/ml).

Unbiased Estimates and Confidence Intervals of Riverine Loads for Low‐Frequency Water Quality Monitoring Strategies

AbstractAccurate estimates of riverine constituent loads are essential for water pollution control and erosion control in watersheds, but an accurate estimation method for commonly employed water quality monitoring strategies, such as calendar‐based sampling with high‐flow sampling, has not been established. Therefore, we propose methods for both unbiased load estimation and confidence interval construction for annual riverine loads using the Horvitz‐Thompson estimator based on limited samples (12 to 20 per year) collected with commonly used water quality monitoring strategies. In addition, we propose an uncertainty reduction method to calculate efficient confidence intervals using probability resampling based on a simple rating curve due to the small sample sizes. The effectiveness of the proposed method is verified by load estimates based on 150 annual data sets of daily pairs of discharge and concentration observations of six water quality parameters from different watersheds and years. The tested sampling strategies include random sampling over time as a proxy for calendar‐based sampling, random sampling with high‐flow sampling, and flow‐proportional sampling. The results show that the proposed methods provide unbiased load estimates for all the data sets and appropriate confidence intervals. The uncertainty reduction in the confidence interval widths obtained with probability resampling is effective for calendar‐based sampling. We also explain the importance of defining proper sampling probabilities for load estimation based on samples with missing observations. The proposed method can be used to evaluate and improve existing water quality monitoring strategies for more efficient load estimation and the retrieval of accurate load estimates from existing data sets.

A quantitative estimation method of ball bearing localized defect size based on vibration instantaneous energy analysis

The quantitative evaluation of bearing damage size is of great significance for accurately predicting the remaining useful life of bearing. Existing studies have shown that rolling elements will produce corresponding vibration features when they enter and leave localized defects, and these features are the premise of accurately estimating the defect size. This paper presents an accurate quantitative estimation method of bearing localized defect size based on vibration instantaneous energy analysis. The time interval of rolling element entry and exit the damaged area is determined by analysing the instantaneous energy of fault impulse. The effectiveness of the proposed method is verified by the experiments of different defect sizes of the outer race and inner race at various speeds. Besides, the proposed method has higher accuracy compared with the conventional methods, which provides a new idea for fast and convenient estimation of the ball bearing localized defect size.

Efficient temperature estimation for thermally stratified storage tanks with buoyancy and mixing effects

Estimating the state thermal storage devices is key to use them efficiently to reduce the uncertainty of renewable sources. Although stratified storage tanks are one of the most efficient and cost-effective storage systems, they lack accurate state estimation methods. In this paper, we propose a general methodology for estimating the state of thermally stratified storage tanks of different topologies and capacity. The method is based on a simple moving horizon estimation technique and a 1-D smooth model that can integrate buoyancy effects into a smooth equation. The novelty of the proposed approach is that it is the first state estimation approach that considers both buoyancy and mixing effects. This distinction is paramount to an adequate estimation of the temperature distribution in the storage tank which can then be used for different aims, namely as a basis for model predictive controls. Besides the novel state estimation approach, the paper has three more contributions: (i) it shows how a model for seasonal storage devices can be further extended to smaller stratified tanks with different topologies; (ii) it modifies such a model so that the model equations can be integrated into a single dynamical equation; (iii) it proposes the most complete case study to date for modeling and estimating temperature distribution inside small stratified storage tanks. The analysis of the proposed approach is done in several stages. First, to validate the applicability of the model to small tanks and multiple topologies, we perform a model identification and parameter estimation for three different stratified tanks. Second, we test the accuracy of the proposed state estimation approach in those three stratified tanks employing the estimated parameters in the first experimental study and the models also previously defined. Finally, to further validate the models, we perform a simulation for each of the three tanks and we compare the accuracy of the simulation against real data. As we show, both the state estimation approach and the model are satisfactorily accurate as they display average mean errors below 2 °C. • We propose a SoC estimation approach for stratified thermal storage vessels. • The approach is the first to include buoyancy and mixing effects using a 1-D model. • We extend the 1-D model for seasonal stratified storage to small stratified tanks. • We proposed the most complete case study for modeling stratified storage tanks.

Estimating the total length of Mekong giant catfish, Pangasianodon gigas, in an aquarium via stereo-video shooting and direct linear transformation.

The Mekong giant catfish (MGC), Pangasianodon gigas, is one of the world's largest catfish species. Endemic to the Mekong River system, the MGC is critically endangered. Six MGC were transported from Thailand to the Gifu World Freshwater Aquarium (GWFA) in Japan in May 2004. The MGC have not been measured since they were introduced to the GWFA due to the challenges associated with their large size. Traditional methods, such as anesthesia and net-capture, could harm the fish, potentially reducing the population further. However, understanding the ecology of the species is essential to conservation efforts. Seasonal feeding rhythms and long-term fasting were previously observed in captive MGCs. To investigate the effect of long-term fasting on MGC growth, total length measurements are necessary. In this study, we applied a noncontact method to estimate the total length via image analysis. We shot a stereo-video of free-swimming MGC in the aquarium tank using two digital video cameras and analyzed the 3D images using the direct linear transformation method. We successfully estimated the total length of each MGC individual without contacting the fish. This accurate estimation method is versatile, simple, and useful in aquarium breeding and is also recommended from the viewpoint of animal welfare because it is a noninvasive method of measurement.

DEVELOPMENT OF REVERSE PHASE HIGH PERFORMANCE LIQUID CHROMATOGRAPHY METHOD FOR SIMULTANEOUS ESTIMATION OF SILDENAFIL CITRATE AND DEPOXETINE HYDROCHLORIDE IN PHARMACEUTICAL FORMULATION

Simple, accurate and precise reversed-phase high-performance liquid chromatographic (RP-HPLC) methods for simultaneous estimation of sildenafil citrate (SIL) and depoxetine hydrochloride (DAP) in combined tablet dosage form have been developed and validated. The RP-HPLC method uses a Shimadzu – 1800, Software Version – UV Prob 2.33 with BDS hypersil C18 column and mixture of Buffer pH 4.0 and ACN in the ratio of 40:60 as the mobile phase. The detection was carried out using a UV–Visible Detector: Shimadzu SPD–20AT diode array detector set at 229 nm. Linearity of chromatographic method was found in the concentration range of 50 - 150 ppm for Sildenafil and 30 - 90 ppm for Dapoxetine respectively. % recovery for SIL was found to be 99.3 – 100.5 %, while for DAP it was found to be in range of 99.1 – 100.4 % in HPLC methods respectively. Both methods may be used for routine analysis of the drugs in a pharmaceutical formulation. Results of analysis were validated statistically. KEYWORDS: Linearity, Validation, HPLC, Sildenafil, Depoxetine.

What is the basis of teacher judgment of student cognitive abilities and academic achievement and what affects its accuracy?

• There is a moderate correlation between teacher’s judgment and pupils' performance. • Judgment is more accurate for academic achievement than cognitive abilities. • Judgment is primarily based on cognitive skills, not academic achievement. • Percentile rating is more accurate than 9-point scale and item-based estimation. • Teacher’s experience, student’s gender, and level of ability do not affect accuracy. The aim of the study was to determine the factors affecting teacher’s judgment accuracy while estimating performance in tests of cognitive abilities and academic achievement of students, and on which student abilities the evaluation was based on. The study included 223 students (38% females) of the fourth grade who were administered the test of cognitive abilities CFT 20-R and the test of academic (mathematical) achievement TIM 3–5 . Their performance was estimated by 10 teachers (8 females) using a 9-point scale and percentile. Furthermore, for a part of the children ( n = 130), 6 of these teachers determined the probability with which the child would correctly solve two particular items of test TIM 3–5 . The most accurate method of estimation is the percentile rating, both for the cognitive abilities ( r = 0.56) and the academic achievement ( r = 0.63). The length of teacher experience and the level of evaluated student ability has no effect on the accuracy of judgment. The student’s gender has no effect on the accuracy of estimation or the level of ascribed ability. Teachers tended to underestimate students in a moderately difficult item of test TIM 3–5 , and overestimate in case of a difficult item. The study further presents a theoretical model in which the teacher’s impression of the student is based on the student’s cognitive abilities and academic achievement. Empirical verification of this model has shown that the basis for teacher’s judgment is primarily the student’s intelligence, which is manifested indirectly in the student’s academic achievement.

Internal Model Control-Based Observer for the Sideslip Angle of an Unmanned Surface Vehicle

Since the sideslip angle is often ignored or simplified in the process of path following of unmanned surface vehicle by using the line-of-sight (LOS) guidance law because of its fast change and the difficulty of measurement, an observer was proposed by internal model control (IMC) to quickly estimate the sideslip angle in the LOS guidance law. First, a prediction model was established for the tracking error, and a state space model for prediction errors was constructed as an internal model. With the introduction of the auxiliary variables, a new augmented system was set up for a state space model of the prediction errors. Then, the sideslip angle observer was designed by the theory of state feedback with the feature of the control law of a proportional-integral type. Theoretically, the stability of the system was proved based on the Lyapunov criteria. A simulation and experiment verified the effectiveness of the proposed sideslip angle observer in improving the path-following accuracy. The results show that the IMC-based observer introduces a proportional term of tracking error that is not considered by other observers, which is easier to implement and adjust, and has a faster response speed and a smaller steady-state error for the sideslip angle. In addition, the assumption of a small sideslip angle is not introduced in the design process, so the proposed observer provides an accurate estimation method for a large sideslip angle.