Speed-sensorless predictive torque controlled induction motor drive with feed-forward control of load torque for electric vehicle applications

Abstract

Nowadays, the global trend is towards reducing CO2 emissions and one solution is to replace internal combustion vehicles with electric vehicles. To this end, electric drive system, the most crucial part of an electric vehicle, has gained importance and has become a major research field. The induction motor (IM) is one of the best candidates for electric vehicle applications due to its advantages such as simple and robust design, low cost and maintenance requirements, the ability to operate in harsh environments. However, it has a highly nonlinear model with time-varying electrical and mechanical parameters making them difficult to control. Finite control set-predictive torque control (FCS-PTC) is an inherently suitable and a promising control method for the IM because FCS-PTC is easy to implement and has the ability to handle nonlinearities with the inclusion of constraints. In addition, the elimination of speed sensors increases the reliability of electric motor drives while reducing cost and hardware complexity. In this paper, a speedsensorless FCS-PTC based IM drive system is designed in order to combine the aforementioned advantages. Unlike the current literature, to improve the torque response of conventional FCS-PTC, the load torque is also estimated by an adaptive fading extended Kalman filter and is fed back into the torque control loop. The results show that improved control performance is achieved.

Speed-Sensorless Predictive Torque Control of the IM Based on MRAS

“…The required 𝑖 𝑠𝛼 , 𝑖 𝑠𝛽 , and 𝜔 𝑚 values are obtained by using the stator current based MRAS structure, which utilizes the current model of the IM to perform 𝜑 𝑟𝛼 and 𝜑 𝑟𝛽 estimations. By estimating 𝜑 𝑟𝛼 and 𝜑 𝑟𝛽 with the help of the current model, the estimated 𝜑 𝑠𝛼 and 𝜑 𝑠𝛽 are obtained for the PTC algorithm as in Equation ( 19) [8]. 17) and ( 18), respectively:…”

“…Here, MPC is rather new comparing to the other methods in the IM control applications. In the literature, one of the most preferred MPC strategies for the control of IMs is the predictive torque control (PTC) [8]. In the PTC strategy, the electromagnetic torque and stator flux are controlled by the proper selection of the voltage vector, which determines the inverter switching states [9].…”

“…Here in PTC, new control constraints and objectives can be added to the cost function [4]. Although there is no need for inner current control loops, there is only one PI controller for the outer speed control loop in PTC [8]. As addressed by Rodriguez et al [4], by considering the computational optimization, the parameter sensitivity, the weight factor adjustment, and the switching frequency limitation, more efficient PTC strategies can be developed.…”

Asenkron Motorların GKF Tabanlı Model Öngörülü Moment Kontrolü

“…Ancak frekans ve sıcaklık gibi ASM'nin çalışma koşulları ile rotor ve stator dirençlerinde meydana gelen bu değişimler, akı ve hız kestirimlerde bozulmalara neden olmaktadır. ASM'lerin yüksek başarımlı hız-algılayıcısız kontrolünü gerçekleştirmek için modele uyarlamalı sistemler (Wang vd., 2014;Xie vd., 2021), kayma kipli (sliding mode) gözlemleyicisi (Lu & Zhao, 2018;Zhao vd., 2019), tam dereceli gözlemleyici (Nguyen vd., 2021;Yin vd., 2019), genişletilmiş Luenberger gözlemleyicisi (Yan & Song, 2020) ve genişletilmiş Kalman filtresi (GKF) (Demir & Barut, 2018;Zerdalı̇ & Demı̇r, 2021) gibi model tabanlı kestiriciler ya da gözlemleyiciler tanıtılmıştır. Literatüre önerilen kestirim yöntemlerinden GKF'ler ölçme gürültülerini göz önünde bulundurarak parametre ve durum kestirim problemini olasıl bir yaklaşım ile gerçekleştirmektedir.…”

Finite Control Set Model Predictive Field-Oriented Control For Three-Phase Induction Motor Drives

“…The induction motor (IM) has become the most popular choice for high-performance industrial applications, electric vehicles, and renewable energy conversion systems (e.g., wind energy). Approximately 90% of the industrial load is shared by the IM because of its simple and resilient design, self-starting characteristics, and requirements for almost little to no maintenance (Zerdali & Demir, 2021) (Abo-Khalil & Sayed, 2021). Thus, a sufficient amount of generated electric power has been utilized by IM around the globe.…”