Rotor resistance estimation ASM

Abstract

Abstract Electric vehicles have experienced a surge in popularity in recent years due to the escalating global importance placed on sustainability. One of the key issues being addressed is the utilization of sustainable materials for electric motors. While certain electric vehicles employ permanent magnet synchronous machines (PMSMs) as their traction motors, these machines rely on rare earth materials. The process of mining rare earth materials is complex and has significant environmental impacts. Consequently, substantial efforts have been directed towards enhancing the performance of induction machines (IMs) to potentially replace PMSMs. A crucial aspect in achieving this goal is the accurate estimation of rotor resistance, which plays a vital role in narrowing the efficiency gap between IMs and PMSMs. The main goal of this thesis was to compare different rotor resistance estimation techniques within a simulation environment. To achieve this, two distinct methods, deemed to be accurate, were tested. The software utilized throughout the thesis was MATLAB/SIMULINK. The first method employed a model reference adaptive system (MRAS), which involved comparing two models (reference and adaptive) to obtain the estimated rotor resistance. The second method relied on high frequency signal injection (HFSI), which affects the commanded reference torque, allowing for the estimation of the rotor resistance. The simulation results obtained using MRAS and HFSI demonstrated successful estimation of the rotor resistance value, each with their respective advantages and disadvantages. One of the significant strengths of using reactive power MRAS is its independence from the stator resistance, which is a parameter subject to variation in real-life scenarios. On the other hand, HFSI offers a non-invasive and cost-effective approach, utilizing existing hardware for implementation. However, caution must be exercised regarding noise interference, as it has the potential to disrupt the frequency of the injected signal and lead to undesired machine behavior.