Design and Implementation of Sensorless Electronic Water Pump for Automobile

Motor Brushless Direct Current (BLDC) has become the preferred choice in various engineering applications. However, BLDC motor control involves high complexity, and motor performance depends on the control algorithms used. This research discusses the use of sensorless control methods, specifically the Sliding Mode Observer (SMO) for rotor position and speed estimation in BLDC motors within the context of Field-Oriented Control (FOC), validated through simulations using Matlab/Simulink. Simulation results indicate that SMO provides rapid dynamic response to current changes, albeit with slight delays at high speeds. Rotor position estimation with SMO is also reasonably accurate in both steady-state and transient conditions, affirming the iveness of SMO in sensorless control for BLDC motors. SMO can be experimentally implemented to enhance sensorless control in BLDC motors by reducing the cost of installing Hall sensors while maintaining comparable performance.

In order to reduce the chattering caused by the discontinuity of the control function in the traditional sliding mode observer (SMO), this article proposes a sliding mode observer with phase-locked loop (PLL) to estimate the speed and position of the rotor. The back electromotive force (EMF) of a permanent magnet synchronous motor (PMSM) in a static coordinate system is accurately estimated by SMO, and then, PLL is constructed to combine the observed rotor position angle and back EMF to compensate the phase lag in angle estimation so as to obtain a more accurate speed. It solves the problems of poor robustness and complex algorithms in the traditional SMO prediction algorithm. The simulation results show that the SMO with PLL can effectively reduce the system chattering and effectively improve the accuracy of rotor speed and position estimation.

This paper presented simulation performance of Brushless DC (BLDC) motor drive using sensorless back EMF (Electro Motive Force) detection technique. Sensorless technique to control BLDC motor is required for different applications. However these motors require hall sensors to detect rotor position, which will further increase cost. There are different sensorless techniques such as inductance varying, flux linkage varying and back emf sensing. Back emf sensing technique is more effective compared to other techniques. So, back emf technique is considered for performance study of BLDC motor. MATLAB Simulink is used to find performance of BLDC motor. The BLDC motor performance is analyzed from various waveforms like back emf, phase current, speed, torque with respect to time at varying loads. The simulation results obtained are satisfactory for sensorless technique.

This article presents the sensorless control of a PMSM based on the FOC (Field Oriented Control) strategy and on PFC (Power Factor Correction), where the rotor speed is provided by speed observers. It presents the block structure of the PFC together with the numerical simulations achieved in Matlab/Simulink, on the improvement of the PF (Power Factor) of the supply circuit. It also presents the block structures of the FOC strategy and of the back-EMF (back electromotive force) sliding mode, MRAS (Model Reference Adaptive System), and PLL (Phase Locked Loop) type observers. The numerical simulations show the superiority of rotor speed estimation when using the back-EMF sliding mode observer compared to the rotor speed estimate provided by MRAS and PLL observers.

This paper presents a method for Permanent magnet synchronous motor (PMSM) drive using Field-Oriented Control (FOC) technology. The rotor speed and current tracking controllers are designed based on backstepping control theory. A Sliding-mode observer (SMO) is used to estimate the back electromotive force under a static frame. After that, a Phase-locked Loop (PLL) is designed to estimate the speed and position of the rotor. The SMO and PLL have robustness against disturbance, high accuracy estimation ability. Moreover, speed and current tracking performance may be affected significantly by the disturbance which is caused by parameter variations and external load torque. So another SMO is presented to estimate the lump disturbance and improve the robustness of the controllers. Finally, the simulation and results are implemented using Matlab/Simulink with Siemens 1KF7 PMSM.

This paper presents a structured and experimentally validated approach to the parameter identification, modeling, and real-time speed control of a brushless DC (BLDC) motor. Electrical parameters, including resistance and inductance, were measured through DC and AC testing under controlled conditions, respectively, while mechanical and electromagnetic parameters such as the back electromotive force (EMF) constant and rotor inertia were determined experimentally using an AVL dynamometer. The back EMF was obtained by operating the motor as a generator under varying speeds, and inertia was identified using a deceleration method based on the relationship between angular acceleration and torque. The identified parameters were used to construct a transfer function model of the motor, which was implemented in MATLAB/Simulink R2024b and validated against real-time experimental data using sinusoidal and exponential input signals. The comparison between simulated and measured speed responses showed strong agreement, confirming the accuracy of the model. A proportional–integral (PI) controller was developed and implemented for speed regulation, using a low-cost National Instruments (NI) USB-6009 data acquisition (DAQ) and a Kelly controller. A first-order low-pass filter was integrated into the control loop to suppress high-frequency disturbances and improve transient performance. Experimental tests using a stepwise reference speed profile demonstrated accurate tracking, minimal overshoot, and robust operation. Although the modeling and control techniques applied are well known, the novelty of this work lies in its integration of experimental parameter identification, real-time validation, and practical hardware implementation within a unified and replicable framework. This approach provides a solid foundation for further studies involving more advanced or adaptive control strategies for BLDC motors.

Variable frequency drives (VFDs) have been used for position sensors for many years. Alternatively, reliable VFDs for smart autonomous systems require the simultaneous configuration of sensors and sensorless operation. This paper details the design and implementation of a continuous fast terminal (CFT) sliding mode controller (SMC) based speed controller and speed estimation through the CFT sliding mode observer (SMO) that accounts for iron loss while calculating total disturbances. The rotor speed dynamics of the PM brushless DC motor (PMBLDCM) drive system is first investigated considering lumped disruption (interference, parametric complexity, and non-linear dynamics). The built-in SMC can control the rotor speed in real time, as well as analyze and compensate for aggregated interruptions in rotor speed dynamics. Additionally, the field-oriented control (FOC) method is developed to maximize torque production while drastically minimizing torque ripples. With this approach, the zero torque pulsation constraint is gradually achieved at a wide speed range. The validation of the proposed CFT-SMC with FOC is carried out using simulation and experiments. According to the comparative study, the proposed sensorless control outperforms conventional methods due to the inclusion of iron loss.

This article presents a sensorless control system based on back-EMF (back electromotive force)sliding mode observer for control of rigid coupling of PMSM multi-motors. The back-EMF $\mathrm{e}_{\alpha}$ and $\mathrm{e}_{\beta}$ are provided by a sliding mode observer in order to estimate the rotor speed and position. The main advantage of the sensorless control consists in eliminating the speed transducers thus contributing to the increased reliability of the entire system. The control structure presented is cascaded, following the FOC (Field Oriented Control)principles, where the inner current loop has the reference I d set to be equal to zero, and the Iq reference is set by the PI-type speed controller in the outer loop. Considering that the load torque distributed to the two motors can be balanced or unbalanced, the main task of the multi-motor PMSM sensorless control system is to maintain the same speed of the slave system and the master system and that both systems match the required speed profile. Real time implementation of the multi-motor PMSM sensorless control system is recommended by the good results obtained from numerical simulations.

ABSTRACTThis paper proposes a new method to detect the initial rotor position at standstill of permanent magnet synchronous motor (PMSM). To estimate rotor position and rotor speed from the back electromotive force (EMF) voltage, we apply sensorless speed control based on sliding-mode observer (SMO). The initial rotor position is detected by using a suitable high-frequency sequence of voltage pulses intermittently applied to the stator windings at standstill. With this approach, we managed to minimise the error on the estimated position to 3.75° electrical degrees without additional materials and uncomplicated calculations. The stability of the proposed SMO was verified using the Lyapunov method. Numerical simulations and experiments demonstrate that the novel SMO method can effectively estimate rotor position and speed with achievement of good static and dynamic performance. The experimental implementation is carried out on powerful dSpace DS1103 controller board based on the digital signal processor (DSP) TMS320F240.

This paper presents a new sliding-mode observer (SMO) for interior permanent-magnet motors (IPM) to be utilized in sensorless field-oriented control (FOC) algorithms. Due to IPM's rotor saliency, the traditional back electromotive force (back-emf) model for surface-mount permanent motors (SPM) cannot be used in IPM observers directly. In order to address this problem, the extended electromotive force (EEMF) model is adopted for observer design. Unlike many other EEMF model based SMOs, the phase delay mitigation algorithm (PDMA) integrated in the proposed observer significantly reduces steady-state estimation error while maintaining low-pass filter's dynamic performance. The simple structure makes the proposed observer an ideal candidate for cost-sensitive applications which guarantees satisfactory performance and efficiency. Theoretical analysis, simulation and experimental results are provided to validate the fidelity of the proposed SMO.

Recently, the role of a BLDC (Brushless Direct Current) motor is favoring the designers due to its higher efficiency. Most of the applications are already using BLDC motors as a replacement for AC motors and this holds true for innumerous applications, and these motors also reduce the overall system weight. The commutation of BLDC motor is done electronically; hence it is quite simple to control the torque and RPM of the motor even at much higher speed. This paper gives a brief comparative study of three different control schemes i.e Sinusoidal field oriented control (FOC), Field oriented control (FOC), Hysteresis control of a BLDC motor primarily on the aspect of output torque ripple. The study of all the three control schemes is discussed briefly and simulation of control algorithm has been performed.

In permanent magnet synchronous motors (PMSMs) sensorless control, the sliding mode observer (SMO) has emerged as a solution for rotor position estimation due to its advantages of high robustness, low cost, and superior dynamic performance. However, the inevitable aperiodic and periodic disturbances present in the control system can induce harmonics in the back electromotive force (EMF), which affect the accuracy of position estimation. Conventional sliding mode observer with low-pass filter (SMO-LPF) inevitably introduces phase lag, parameter sensitivity, and signal discontinuity issues. This paper proposes a novel composite controller that combines enhanced repetitive control (ERC) and SMO. The method utilizes the periodic signal suppression capability of repetitive control (RC) to compensate for the harmonics of current, thereby reducing the interference of low-order harmonics on position observation. Additionally, approach ensures the stability of the sliding mode while retaining the strong robustness of the SMO. The simulation results demonstrate that the proposed controller exhibits excellent harmonic suppression capability in terms of magnitude-frequency characteristics. Furthermore, comprehensive simulation experiments including dynamic response analysis, robustness testing, and speed estimation accuracy verification have conclusively validated the effectiveness of the novel approach.

The electric vehicle’s overall efficiency can be augmented through the implementation of the regenerative braking system (RBS), which serves to extend the drive range. This paper explores a method for further increasing said range by implementing a roof‐mounted photovoltaic (PV) system in conjunction with RBS, resulting in an impressive 25.14% increase to the vehicle’s driving distance. The roof‐mounted PV and regenerative braking work together to charge the dual battery pack present within the vehicle, following a specific sequence as dictated by its controller. Maximum energy is extracted from the PV module via employment of a particle swarm optimization (PSO)‐based maximum power point tracking (MPPT) algorithm, while propulsion is provided through utilization of a brushless direct current (BLDC) motor driven by reduced switch voltage source inverter (VSI). The BLDC motor itself is controlled utilizing field‐oriented control (FoC), with hybrid ANN‐PID and Fuzzy‐PID (HAP‐FUP) controllers employed at the outer loop; furthermore, HAP‐FUP controller performance was compared favorably against other top controllers such as model predictive controller (MPC), sliding mode controller (SMC), and conventional PID controller, ultimately demonstrating superior performance when it comes to reducing rise time and settling time of vehicle speed.

Brushless DC (BLDC) Motor is widely used in home appliance, robot, and vehicle industry due to the merits of high power density, low noise, and simple controllability. A demands for the motor, especially slim-type BLDC motor, is expected to increase continuously since the minimizing trend of the actuators is getting attention from various applications. Because a phase inductance of the slim-type BLDC motor is large, it causes a lagging of current compared with back-electromotive force (EMF) in wide range of speed. As a result, there is a problem that reduces the motor efficiency and increases the phase current. Particularly the problem is more serious in high speed range and heavy load condition. This paper proposed control scheme for high efficiency of slim type BLDC motor which can resolve the problems as mentioned above. To synchronize the phase between the current and back-EMF of BLDC motor, it proposed lead angle control method by using current dynamics characteristic. Also, it represented the accurate calculating method of lead angle by using only the maximum value of phase current and information of DC-link voltage. For the verification of the proposed control scheme, various simulations and experiments are employed. As a result, the efficiency improvement of slim type BLDC motor is confirmed.

Brushless direct current (BLDC) motors are frequently used in dynamic applications. A Brushless DC Motor is similar to a Brushed DC Motor, except that as the names indicate, they are electronically commutated rather than using brushes for commutation. Brushes are utilized in conventional brushed direct current motors to transmit power to the rotor while they rotate in a fixed magnetic field. Small Brushless DC Motors have flourished as a result of current power electronics and microprocessor technology, both in terms of price and performance. This paper will discuss the history of BLDC motors, their different types, construction, operating principles, and several control mechanisms for driving BLDC motors in various industrial applications. Keywords: BLDC Motor, Pulse Width Modulation (PWM), Hall Effect Sensors, Sensorless control, Rotor, Stator, Back Emf, Trapezoidal Control, Sinusoidal Control, Field Oriented Control