Adaptive control of sinusoidal brushless DC motor actuators

Electrical Power Assisted Steering system (EPAS) will likely be used on future automotive power steering systems. The sinusoidal brushless DC (BLDC) motor has been identified as one of the most suitable actuators for the EPAS application. Motor characteristic variations, which can be indicated by variations of the motor parameters such as the coil resistance and the torque constant, directly impart inaccuracies in the control scheme based on the nominal values of parameters and thus the whole system performance suffers. The motor controller must address the time-varying motor characteristics problem and maintain the performance in its long service life. In this dissertation, four adaptive control algorithms for brushless DC (BLDC) motors are explored. The first algorithm engages a simplified inverse dq-coordinate dynamics controller and solves for the parameter errors with the q-axis current (iq) feedback from several past sampling steps. The controller parameter values are updated by slow integration of the parameter errors. Improvement such as dynamic approximation, speed approximation and Gram-Schmidt orthonormalization are discussed for better estimation performance. The second algorithm is proposed to use both the d-axis current (id) and the q-axis current (iq) feedback for parameter estimation since id always accompanies iq. Stochastic conditions for unbiased estimation are shown through Monte Carlo simulations. Study of the first two adaptive algorithms indicates that the parameter estimation performance can be achieved by using more history data. The Extended Kalman Filter (EKF), a representative recursive estimation algorithm, is then investigated for the BLDC motor application. Simulation results validated the superior estimation performance with the EKF. However, the computation complexity and stability may be barriers for practical implementation of the EKF. The fourth algorithm is a model reference adaptive control (MRAC) that utilizes the desired motor characteristics as a reference model. Its stability is guaranteed by Lyapunov’s direct method. Simulation shows superior performance in terms of the convergence speed and current tracking. These algorithms are compared in closed loop simulation with an EPAS model and a motor speed control application. The MRAC is identified as the most promising candidate controller because of its combination of superior performance and low computational complexity. A BLDC motor controller developed with the dq-coordinate model cannot be implemented without several supplemental functions such as the coordinate transformation and a DC-to-AC current encoding scheme. A quasi-physical BLDC motor model is developed to study the practical implementation issues of the dq-coordinate control strategy, such as the initialization and rotor angle transducer resolution. This model can also be beneficial during first stage development in automotive BLDC motor applications.

THERMAL CHARACTERIZATION OF A GASOLINE TURBOCHARGED DIRECT INJECTION (GTDI) ENGINE UTILIZING LEAN OPERATION AND EXHAUST GAS RECIRCULATION (EGR)

The push for improved fuel economy and reduced emissions has led to great achievements in engine performance and control. These achievements have increased the efficiency and power density of gasoline engines dramatically in the last two decades. With the added power density, thermal management of the engine has become increasingly important. Therefore it is critical to have accurate temperature and heat transfer models as well as data to validate them. With the recent adoption of the 2025 Corporate Average Fuel Economy(CAFE) standard, there has been a push to improve the thermal efficiency of internal combustion engines even further. Lean and dilute combustion regimes along with waste heat recovery systems are being explored as options for improving efficiency. In order to understand how these technologies will impact engine performance and each other, this research sought to analyze the engine from both a 1st law energy balance perspective, as well as from a 2nd law exergy analysis. This research also provided insights into the effects of various parameters on in-cylinder temperatures and heat transfer as well as provides data for validation of other models. It was found that the engine load was the dominant factor for the energy distribution, with higher loads resulting in lower coolant heat transfer and higher brake work and exhaust energy. From an exergy perspective, the exhaust system provided the best waste heat recovery potential due to its significantly higher temperatures compared to the cooling circuit. EGR and lean combustion both resulted in lower combustion chamber and exhaust temperatures; however, in most cases the increased flow rates resulted in a net increase in the energy in the exhaust. The exhaust exergy, on the other hand, was either increased or decreased depending on the location in the exhaust system and the other operating conditions. The effects of dilution from lean operation and EGR were compared using a dilution ratio, and the results showed that lean operation resulted in a larger increase in efficiency than the same amount of dilution with EGR. Finally, a method for identifying fuel spray impingement from piston surface temperature measurements was found. Note: The material contained in this section is planned for submission as part of a journal article and/or conference paper in the future.