Performance Estimation Model of a Torque Converter Part I: Correlation between the Internal Flow Field and Energy Loss Coefficient

김범수,임원식,차석원,하승범 한국자동차공학회 2008 International journal of automotive technology Vol.9 No.2

The objective of this paper is to improve the performance estimation model of the internal flow field of a torque converter. Compared with performance experiment results, the converter based on the one-dimensional model does not satisfy the performance requirements demanded in practice. Therefore, we need to develop more predictable and reliable performance estimation models. In order to obtain shape information on three-dimensional blade geometry, a process of reverse engineering conducts a torque converter assembly, impeller, turbine and stator. In addition, a CFD simulation including mesh generation and post-processing was carried out to extract equivalent parameters from the internal flow field. The internal flow field can be explained by analyze the correlation between a performance estimation model and CFD analysis. The equivalent performance model adopts the variation of energy loss coefficients for a given operating condition according to the application of a changing energy loss coefficient by the least mean squares method. The estimated equivalent model improves the agreement in performance between experiments and the theoretical model. This model can reduce the error to within about 3 percent. Furthermore, this procedure for predicted performance achieves eminence in the estimation of the capacity factor. The objective of this paper is to improve the performance estimation model of the internal flow field of a torque converter. Compared with performance experiment results, the converter based on the one-dimensional model does not satisfy the performance requirements demanded in practice. Therefore, we need to develop more predictable and reliable performance estimation models. In order to obtain shape information on three-dimensional blade geometry, a process of reverse engineering conducts a torque converter assembly, impeller, turbine and stator. In addition, a CFD simulation including mesh generation and post-processing was carried out to extract equivalent parameters from the internal flow field. The internal flow field can be explained by analyze the correlation between a performance estimation model and CFD analysis. The equivalent performance model adopts the variation of energy loss coefficients for a given operating condition according to the application of a changing energy loss coefficient by the least mean squares method. The estimated equivalent model improves the agreement in performance between experiments and the theoretical model. This model can reduce the error to within about 3 percent. Furthermore, this procedure for predicted performance achieves eminence in the estimation of the capacity factor.

Biped robot state estimation using compliant inverted pendulum model

Bae, Hyoin,Oh, Jun-Ho Elsevier 2018 Robotics and autonomous systems Vol.108 No.-

<P><B>Abstract</B></P> <P>This study proposes a biped robot state estimation framework based on a compliant inverted pendulum model and a robust state estimator. A proper model that can express the key physical characteristics while considering limited computing power should be defined for the biped robot state estimation. A biped robot’s limited structural stiffness and relatively long legs compared with the cross section of the body lead to undesired flexibility. However, the models used in previous research are either not suitable for state estimation or too simple to express the essential characteristics of the biped robot. A compliant inverted pendulum model is adopted herein to enhance the estimation accuracy. This model is made by adding a virtual spring and a damper to the conventional inverted pendulum. The additional elements represent the mechanical deformation and the undesired flexible movement. Adopting this model makes it possible to reflect the important characteristics of the biped robot while taking advantage of the merits of the single-mass model. In addition, a robust state estimator that we previously proposed is adopted to compensate for the estimation error caused by the modeling error. Using these two factors, the improved COM-kinematics estimate is obtained with respect to the existing simple-model-based biped state estimators.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Humanoid robot has the flexibility feature and this disturbs the state estimation. </LI> <LI> A compliant inverted pendulum model is adopted to reflect the robot’s key feature. </LI> <LI> The previously developed robust estimator is utilized to enhance the performance. </LI> <LI> Compliant model and robust estimator based state estimation framework is suggested. </LI> </UL> </P>

국내 대형점의 매출추정모델 설정 방안 연구

윤명길,김종진,박철주,심규열 한국유통과학회 2013 유통과학연구 Vol.11 No.12

Purpose- The purpose of this study was to construct a turn over estimation model by investigating research by Park et al. (2006) on the market area of domestic distribution. The study investigated distribution by using a new tool for the turnover estimation technique. This study developed and discussed the turnover estimation technique of Park et al. (2006), applying it to a large-scale retailer in “D”city that was suitable for on-the-spot distribution. It constructed the new model in accordance with test procedures keeping to this retail business location, to apply its procedures to a specific situation and improve the turn over estimation process. Further, it investigated the analysis and procedures of existing turnover estimation cases to provide problems and alternatives for turnover estimation for a large-scale retailer in “D”city. Finally, it also discussed problems and scope for further research. Research design, data, and methodology- This study was conducted on the basis of “virtue” studies. In other words, it took into account the special quality of the structure of Korea's trade zones. The researcher sought to verify a sale estimate model for use in a distribution industry’s location. The main purpose was to enable the sale estimate model (that is, the individual model's presentation) to be practically used in real situations in Korea by supplementing processes and variables. Results- The sale estimate model is constructed, first, by conducting a data survey of the general trading area. Second,staying within the city’s census of company operating areas, the city’s total consumption expenditure is derived by applying the large-scale store index. Third, the probability of shopping is investigated. Fourth, the scale of sales is estimated using the process of singularity. The correct details need to be verified for the model construction and the new model will need to be a distinct sale estimate model, with this being a special quality for business conditions. This will need to be a subsequent research task. Conclusions- The study investigated, tested, and supplemented the turnover estimation model of Park et al. (2006) in a market area in South Korea. Supplementation of some procedures and variables could provide a turnover estimation model in South Korea that would be an independent model. The turnover estimation model is applied, first, by undertaking an investigation of the market area. Second, a census of the intercity market area is carried out to estimate the total consumption of the specific city. Consumption is estimated by applying indexes of large-scale retailers. Third, an investigation is undertaken on the probability of shopping. Fourth, the scale of turnover is estimated. Further studies should investigate each department as well as direct and indirect variables. The turnover estimation model should be tested to construct new models depending on the type of region and business. In-depth and careful discussion by researchers is also needed. An upgraded turnover estimation model could be developed for Korea’s on-the-spot distribution.

확률적 머신러닝 모델기반의 리튬이온배터리 파라미터 추정 알고리즘

김민호(Minho Kim),송민석(Minseok Song),임정택(Jeongtaek Lim),함경선(Kyung Sun Ham),이도헌(DOHEON LEE),김태형(Taehyoung Kim) 한국에너지학회 2024 에너지공학 Vol.33 No.1

In this study, a new lithium-ion battery performance degradation model and a stochastic machine learning model-based lithium-ion battery parameter estimation method were proposed and verified through actual battery degradation cycle experiment data. The proposed parameter estimation method based on a stochastic machine learning model requires less battery model operation time compared to other methods, enabling efficient parameter estimation. The lithium-ion battery performance degradation model is an equivalent circuit-based model, but it reflects various electrochemical phenomena, including side reactions on the surface of the anode active material, including the formation of a solid electrolyte interphase (SEI) layer, the loss of positive electrode active material due to mechanical stress-induced fatigue failure is included, and the corresponding decrease in the amount of cyclable lithium. In the proposed method of estimating the parameters of a lithium-ion battery model, a probabilistic machine learning model that can estimate battery model parameters from sensible data such as voltage and current is developed and used to generate virtual experiment data. We proposed a technique for learning and finding optimal battery model parameters based on the learned model. The developed performance degradation model and parameter estimation method were verified based on actual experimental data. Since it is impossible to observe the inside of the battery, correct answers to the battery parameters cannot be obtained, so the model and parameter estimation algorithm are indirectly verified through errors of voltage and temperature. As a result of the verification, the errors in voltage and temperature were found to be 0.676% and 0.207%, respectively.

기업의 조세부정예측모형에 관한 연구

박현재 ( Hyun Jae Park ),김갑순(교신저자) ( Kap Soon Kim ) 한국회계학회 2016 회계저널 Vol.25 No.3

본 연구는 국내 기업의 회계자료 및 기업특성을 이용하여 조세부정 정도를 추정하는 모형을 제시하고, 예측모형의 구체적인 활용방안을 설명하였다. 구체적으로, 2000년부터 2013년까지 세무조사로 적발되어 전자공시시스템(DART)에 공시한 12월 결산 상장법인과 대응표본을 대상으로 100회 무작위추출에 의한 단계적 로짓분석(stepwise logisticregression)을 실시하여 조세부정 예측모형을 추정하였다. 최종 예측모형에는 유효세율, 부채비율, 수출비율, 매출액, 회계이익과 과세소득의 차이, 재벌여부, 감사인 규모의 7개 변수가 포함되었다. 분석결과, 국내 상장기업들은 유효세율, 부채비율, 매출액이 높을수록 조세부정 가능성이 높았으며, 반면 수출비율, 회계이익과 과 세소득의 차이가 낮을수록 조세부정 가능성이 높은 것으로 나타났다. 또한 재벌에 소속되어 있으며 외부감사인이 Non-Big4인 경우에 조세부정 가능성이 높았다. 본 연구의 예측모형은 모든 기업을 비부정기업으로 가정하는 단순전략과 비교하여 총기대오류비용을 크게 감소시킬 수 있는 것으로 나타나 비용효율적임을 제시하였다. 재무제표와 기업특성 자료만을 필요로 하는 본 연구의 예측모형은 과세당국, 학계, 외부감사인, 투자자들이 특정 기업의 조세부정 가능성을 일차적으로 평가하는데 유용할 것으로 기대된다. Tax fraud affects the national budget to reduce the tax revenues of the country. Lisowsky(2010) is, U.S. Treasury(1999) with reference to the report, it reported that tax revenues that the federal government will be lost in the tax evasion has reached 10 billion dollars a year. In Korea, there is a trend that is collected additionally the number of tax audits and the amounts collected additionally associated with increased offshore tax evasion annually. Domestic and foreign tax authorities are making various efforts to prevent such these tax fraud. U.S. Internal Revenue Service(IRS) in 2000 to tax fraud transactions(tax shelter) dedicated to agencies(the Office of Tax Shelter Analysis, OTSA) established by the tax fraud monitoring and there. Even concluded in the domestic Foreign Account Tax Compliance Act(FATCA) from September 2015 agreed to strengthen offshore tax evasion blocked by the U.S. Internal Revenue Service(IRS) through the financial information exchange. Many studies theoretically explain and empirically analyze relevance of between of corporate tax burden level, financial characteristics, corporate governance, book to tax income differences and tax avoidance. In addition, previous studies related to tax evasion has focused to analyze the differences between the various properties compared to the corporate tax fraud caught by the companies. However, can be utilized in practice, decisions regarding models and tax evasion about to estimate the extent of tax evasion of specific companies, remains a substantial portion unsolved problem. In this study, while presenting a predictive model that can determine whether to tax fraud, the specific manner of utilization of the model is trying to explore. In particular, an attempt to estimate a more sophisticated predictive models, comprehensive consideration tax avoidance and financial characteristics that it has been confirmed that affect the tax evasion, ownership and governance structure characteristics, the external auditor of the properties are in the previous research did. Specifically, the effective tax rate, company size, profitability, ratio of assets investment, debt ratio, export ratio, sales, financial constraints, discretionary accruals, research and development expenses, of the difference between profit and taxable income on eleven numbers of financial characteristic variables, ownership interest rate, foreign interest rates, jaebul, whether three of ownership and characteristic variables of the governance structure, the auditor scale of one of the external auditor of the characteristic variables to the consideration stepwise logistic regression was utilized to derive the final predictive model. In order to eliminate the estimated arbitrariness of the estimation model, 50 percent of the entire sample to predict the estimation sample in the random sampling method, and the remaining 50 percent and holdout samples. Further, in order to solve one of the reliability issues due to random sampling, 100 times and randomly, and extracted the available variables in predictive model. By using the validation sample in order to verify the suitability of the estimated prediction model, to derive the tax fraud probability of tax fraud corporate and non-fraud corporate, tax fraud probability of tax fraud company has verified whether significantly higher. Further, we is trying to verification of the economic efficiency of tax fraud estimation model by comparing the total expected cost when using the predictive model or not by the methodology of Beneish(1997), Ko and Yoon(2006). This study develops a model to detect tax fraud using a sample of firms identified as tax fraud by the Financial Supervisory Service of Korea and characteristics of corporate for the period from 2000 to 2013. We find seven useful variables: tax expense/pretax book income(ETR); debt/total asset(LEV); export proceeds/total sales(EXPORT); log(total sales)(SALES); book-tax difference/total asset(BTD); jaebul(GROUP); auditor size(BIG4). Results suggest that Korean firms are more likely to manipulate taxable income when ETR, LEV, SALES are more larger and EXPORT, BTD are more smaller and these firms are GROUP and audited by Non-Big4. Compared with a naive strategy of classifying all firms as non-manipulators, our estimation model is expected to significantly reduce costs of misclassification. Tax regulator, academic, external auditors, investor, and other users of financial statements might use our model to screen potential tax fraud, to which they can allocate additional resources for more in-depth analysis.

XGBoost를 활용한 리스크패리티 자산배분 모형에 관한 연구

김영훈(Younghoon Kim),최흥식(HeungSik Choi),김선웅(SunWoong Kim) 한국지능정보시스템학회 2020 지능정보연구 Vol.26 No.1

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

특집논문 : 구조방정식모형의 문제점과 해결 방안 ; 공분산구조분석의 모형추정 절차: 방법론적 진단 및 처방

김상욱 ( Sang Wook Kim ) 한국조사연구학회 2016 조사연구 Vol.17 No.1

이 글은 공분산구조분석을 시도할 때 과연 어떠한 모형추정 절차를 따라야만 하는가 하는 방법론적 이슈와 관련한 국내 기존연구들의 문제점을 짚어내고 해법을 모색하려는 목적으로 준비되었다. 특별히 이 글에서는 구조방정식모형을 통계적으로 추정해 내는 세부적 과정과 절차에 있어서 국내연구들이 올바른 방법론적 전형 및 규준으로부터 어떻게 그리고 얼마나 이탈되어 있는가의 관점에서 문제점을 진단하고 방법론적 처방을 제시하고자 하였다. 모형추정의 주요 단계별로 논의한 방법론적 규준 및 처방은 모두네 가지였는데, 구체적으로 (1) 본격적인 모형추정에 앞서는 사전적 정지작업으로서의 문항분석(내적 일관성 검증 및 탐색적 요인분석), 그리고 다중공선성 검증 및 확인적 요인분석, (2) 소위 ‘2단계 접근법’으로서의 측정모형과 구조모형의 개별적·순차적 추정, (3) 구조모형의 주요 인과경로 계수를 추정함에 있어서 초기모형으로 간명모형을 선택한 후 점진적·부가적으로 경로를 설정해 나가는 보수적 추정전략, (4) 측정오차들 상호간 독립성이라는 핵심적 통계적 전제에 대한 적극적인 전방위적 검증 및 반영 등이 그것이다. 이러한 규준 및 처방에도 불구하고 대부분의 국내 연구들은 (1) 본격적 모형추정에 앞서서 문항분석 등을 세밀하게 시도하지 않아서 사상누각의 결과를 가져오며, (2) ‘2단계 접근법’을 제대로 적용하지 않음으로써 ‘해석적 혼란’뿐 아니라 상관관계와 인과관계 상호간 ‘혼란’없는 얼개를 적절히 보여주지 못하고, (3) 간명모형으로 시작하는 이론적·선험적 접근전략을 구사하기보다는 포화모형으로 시작해서 경험적 기준에 과도하게 집착하는 경험경도적 전략을 동원함으로써 몰(沒)이론적이고 사후소급가설화에 의존하는 경향이 있으며, (4) 측정오차들 상호간 독립성과 관련한 통계적 전제를 별도로 검증하지도 또는 아예 관심조차 보이지 않음으로써 모형추정 결과에 각종 오류를 초래하는 문제를 나타냄을 지적하였다. 여타 통계분석기법들과 차별화되는 공분산구조분석 기법 고유의 장점 그리고 최근 점증하는 활용 추세에도 불구하고 상당수의 국내 연구들은 적확한 방법론적 이해와 적용절차를 결여함으로써 이 기법의 장점을 극대화하기보다는 오히려 오 남용 가능성을 크게 경계하여야 할 상황임을 강조하였다. This study tries to address methodological issues concerning what kind of estimation procedures needs to be employed in estimating causal models in the covariance structure analysis. In particular, special attention is paid to try to diagnose detailed sorts of problems prevalent in the extant literature in Korea, and also to provide a proper prescription to help avoid or rectify such problems. To be more precise, a total of four protocols or criteria are suggested to be adhered to, in sequence, in the process of model estimation: (1) as a beforehand job to prepare for the main or full-fledged estimation of causal model, detailed ``item analysis`` should be conducted to check into the internal consistency and discriminant-convergent validity; (2) the so-called ``two-step approach’ needs to be used to try to estimate the measurement and structural models on a separate and sequential basis; (3) the conservative strategy needs to be used by means of adopting an over-identified, or parsimonious, model as a baseline structural model and then trying to free up some of the remaining, unspecified causal paths merely one by one based primarily on their theoretical plausibility; (4) the critical statistical assumption relating to correlated measurement errors among the measurement variables needs to be strictly tested for and incorporated into the main analysis. Despite these protocols or criteria, a substantial body of literature using the covariance structure analysis in Korea are indeed: (1) failing to conduct the item analysis carefully prior to the estimation of causal model; (2) failing to use the two step approach appropriately; (3) failing to use the theory-driven, conservative strategy, and having tended to use, instead, the data driven, a theoretical strategy; (4) failing to test the assumption of correlated measurement errors in estimating the structural model. Methodological and substantial ramifications stemming from these problems are discussed in further details to guard against the possibility of serious misuses or abuses of such analytic technique in Korea.

GRU 배터리 모델 기반 SOC 추정기 설계

김주희(Juhui Gim),최완식(Wansik Choi),안창선(Changsun Ahn) 한국자동차공학회 2022 한국 자동차공학회논문집 Vol.30 No.1

Estimating the State of Charge(SOC) is essential in the efficient battery management of electric vehicles. The mainstream method for SOC estimation is model-based filtering, while the battery model accuracy determines the SOC estimation accuracy. The generally applied battery model for SOC estimation is an Equivalent Circuit Model(ECM), a simplified version of the complex battery structure, but it requires circuit parameters. This paper proposes the parameter-free, data-driven battery model, and designs a SOC estimator by using the proposed battery model and the Unscented Kalman Filter(UKF). The GRU-based battery model trains the battery internal states by using the applied current and the measured voltage with the Gated Recurrent Units(GRU)-based structure, without prior knowledge of the battery. The UKF is introduced as an SOC estimator by using the proposed high nonlinear battery model. The proposed SOC estimator is validated by comparing the ECM model-based UKF, and showed the possibility of SOC estimation without the battery parameters.

다중모델추정기법을 이용한 HEV/EV용 리튬이온전지의 잔존충전용량 추정

정해봉(Hae-Bong Jung),김영철(Young-Chol Kim) 대한전기학회 2011 전기학회논문지 Vol.60 No.1

This paper presents a new state of charge(SOC) estimation of large capacity of Li-ion battery (LIB) based on the multiple model adaptive estimation(MMAE) method. We first introduce an equivalent circuit model of LIB. The relationship between the terminal voltage and the open circuit voltage(OCV) is nonlinear and may vary depending on the changes of temperature and C-rate. In this paper, such behaviors are described as a set of multiple linear time invariant impedance models. Each model is identified at a temperature and a C-rate. These model set must be obtained a priori for a given LIB. It is shown that most of impedances can be modeled by first-order and second-order transfer functions. For the real time estimation, we transform the continuous time models into difference equations. Subsequently, we construct the model banks in the manner that each bank consists of four adjacent models. When an operating point of cell temperature and current is given, the corresponding model bank is directly determined so that it is included in the interval generated by four operating points of the model bank. The MMAE of SOC at an arbitrary operating point (T ℃, Ibat[A]) is performed by calculating a linear combination of voltage drops, which are obtained by four models of the selected model bank. The demonstration of the proposed method is shown through simulations using DUALFOIL.

변형확률모델을 활용한 소매업의 상권분석 방안에 관한 연구

진창범,윤명길 한국유통과학회 2017 유통과학연구 Vol.15 No.6

Purpose – This study aims to develop correspondence strategies to the environment change in domestic retail store types. Recently, new types of retails have emerged in retail industries. Therefore, trade area platform has developed focusing on the speed of data, no longer trade area from district border. Besides, ‘trade area smart’ brings about change in retail types with the development of giga internet. Thus, context shopping is changing the way of consumers’ purchase pattern through data capture, technology capability, and algorithm development. For these reasons, the sales estimation model has been shown to be flawed using the notion of former scale and time, and it is necessary to construct a new model. Research design, data, and methodology – This study focuses on measuring retail change in large multi-shopping mall for the outlook for retail industry and competition for trade area with the theoretical background understanding of retail store types and overall domestic retail conditions. The competition among retail store types are strong, whereas the borders among them are fading. There is a greater need to analyze on a new model because sales expectation can be hard to get with business area competition. For comprehensive research, therefore, the research method based on the statistical analysis was excluded, and field survey and literature investigation method were used to identify problems and propose an alternative. In research material, research fidelity has improved with complementing research data related with retail specialists’ as well as department stores. Results – This study analyzed trade area survival and its pattern through sales estimation and empirical studies on trade areas. The sales estimation, based on Huff model system, counts the number of households shopping absorption expectation from trade areas. Based on the results, this paper estimated sales scale, and then deducted modified probability model. Conclusions – In times of retail store chain destruction and off-line store reorganization, modified Huff model has problems in estimating sales. Transformation probability model, supplemented by the existing problems, was analyzed to be more effective in competitiveness business condition. This study offers a viable alternative to figure out related trade areas’ sale estimation by reconstructing new-modified probability model. As a result, the future task is to enlarge the borders from IT infrastructure with data and evidence based business into DT infrastructure.