Research and Implement of PMSM Regenerative Braking Control for Electric Vehicle

As the society pays more and more attention to the environment pollution and energy crisis, the electric vehicle (EV) development also entered in a new era. With the development of motor speed control technology and the improvement of motor performance, although the dynamic performance and economical cost of EVs are both better than the internal-combustion engine vehicle (ICEV), the driving range limit and charging station distribution are two major problems which limit the popularization of EVs. In order to extend driving range for EVs, regenerative braking (RB) emerges which is able to recover energy during the braking process to improve the energy efficiency. This thesis aims to investigate the RB based pure electric braking system and its implementation. There are many forms of RB system such as fully electrified braking system and blended braking system (BBS) which is equipped both electric RB system and hydraulic braking (HB) system. In this thesis the main research objective is the RB based fully electrified braking system, however, RB system cannot satisfy all braking situation only by itself. Because the regenerating electromagnetic torque may be too small to meet the braking intention of the driver when the vehicle speed is very low and the regenerating electromagnetic torque may be not enough to stop the vehicle as soon as possible in the case of emergency braking. So, in order to ensure braking safety and braking performance, braking torque should be provided with different forms regarding different braking situation and different braking intention. In this thesis, braking torque is classified into three types. First one is normal reverse current braking when the vehicle speed is too low to have enough RB torque. Second one is RB torque which could recover kinetic energy by regenerating electricity and collecting electric energy into battery packs. The last braking situation is emergency where the braking torque is provided by motor plugging braking based on the optimal slip ratio braking control strategy. Considering two indicators of the RB system which are regenerative efficiency and braking safety, a trade-off point should be found and the corresponding control strategy should be designed. In this thesis, the maximum regenerative efficiency is obtained by a braking torque distribution strategy between front wheel and rear wheel based on a maximum available RB torque estimation method and ECE-R13 regulation. And the emergency braking performance is ensured by a novel fractional-order integral sliding mode control (FOISMC) and numerical simulations show that the control performance is better than the conventional sliding mode controller

Speed control of an SPMSM using a tracking differentiator-PID controller scheme with a genetic algorithm

In this paper, a tracking differentiator-proportional integral and derivative (TD-PID) control scheme is proposed to control the speed of a surface mount permanent magnet synchronous motor (SPMSM). The TD is used to generate the necessary transient profile for both the reference and the output speed, which are compared with each other to produce the error signals that feed into the PID controller. In addition to the TD unit parameters, the PID controller’s parameters are tuned to achieve the optimum new multi-objective performance index, comprised of the integral of the time absolute error (ITAE), the absolute square of the control energy signal (USQR), and the absolute value of the control energy signal (UABS) and utilizing a genetic algorithm (GA). A nonlinear model of the SPMSM is considered in the design and the performance of the proposed TD-PID scheme was validated by comparing its performance with that of a traditional PI controller in a MATLAB environment. Different case studies were tested to show the effectiveness of the proposed scheme, results including peak overshoot, energy consumption, control signal chatter, and 30% improvement in the OPI, with variable reference speeds, load torque, and parameters uncertainties. Illustrate the proposed scheme's success compared with PI controller

PSO BASED TAKAGI-SUGENO FUZZY PID CONTROLLER DESIGN FOR SPEED CONTROL OF PERMANENT MAGNET SYNCHRONOUS MOTOR

A permanent magnet synchronous motor (PMSM) is one kind of popular motor. They are utilized in industrial applications because their abilities included operation at a constant speed, no need for an excitation current, no rotor losses, and small size. In the following paper, a fuzzy evolutionary algorithm is combined with a proportional-integral-derivative (PID) controller to control the speed of a PMSM. In this structure, to overcome the PMSM challenges, including nonlinear nature, cross-coupling, air gap flux, and cogging torque in operation, a Takagi-Sugeno fuzzy logic-PID (TSFL-PID) controller is designed. Additionally, the particle swarm optimization (PSO) algorithm is developed to optimize the membership functions' parameters and rule bases of the fuzzy logic PID controller. For evaluating the proposed controller's performance, the genetic algorithm (GA), as another evolutionary algorithm, is incorporated into the fuzzy PID controller. The results of the speed control of PMSM are compared. The obtained results demonstrate that although both controllers have excellent performance; however, the PSO based TSFL-PID controller indicates more superiority

A novel adaptive PD-type iterative learning control of the PMSM servo system with the friction uncertainty in low speeds

High precision demands in a large number of emerging robotic applications strengthened the role of the modern control laws in the position control of the Permanent Magnet Synchronous Motor (PMSM) servo system. This paper proposes a learning-based adaptive control approach to improve the PMSM position tracking in the presence of the friction uncertainty. In contrast to most of the reported works considering the servos operating at high speeds, this paper focuses on low speeds in which the friction stemmed deteriorations become more obvious. In this paper firstly, a servo model involving the Stribeck friction dynamics is formulated, and the unknown friction parameters are identified by a genetic algorithm from the offline data. Then, a feedforward controller is designed to inject the friction information into the loop and eliminate it before causing performance degradations. Since the friction is a kind of disturbance and leads to uncertainties having time-varying characters, an Adaptive Proportional Derivative (APD) type Iterative Learning Controller (ILC) named as the APD-ILC is designed to mitigate the friction effects. Finally, the proposed control approach is simulated in MATLAB/Simulink environment and it is compared with the conventional Proportional Integral Derivative (PID) controller, Proportional ILC (P-ILC), and Proportional Derivative ILC (PD-ILC) algorithms. The results confirm that the proposed APD-ILC significantly lessens the effects of the friction and thus noticeably improves the control performance in the low speeds of the PMSM

Application of Sliding Mode Controller and Linear Active Disturbance Rejection Controller to a PMSM Speed System

Permanent magnet synchronous motor (PMSM) is a popular electric machine in industry for its small volume, high electromagnetic torque, high reliability and low cost. It is broadly used in automobiles and aircrafts. However, PMSM has its inherent problems of nonlinearity and coupling, which are challenges for control systems design. In addition, the external disturbances such as load variation and noises could degrade the systems performance. Both sliding mode control (SMC) and active disturbance rejection control (ADRC) are robust against disturbances. They can also compensate the nonlinearity and couplings of the PMSM. Therefore, in this thesis, we apply both SMC and ADRC to a PMSM speed system. Our control goal is to drive the speed outputs of the PMSM speed system to reference signals in the presences of nonlinearity, disturbance, and parameter variations. Simulation results verify the effectiveness of SMC and ADRC on the speed control for PMSM systems in spite of the presences of external disturbance and internal system uncertaintie

Linear matrix inequality based synthesis of PI controllers for PMSM with uncertain parameters

This paper addresses the design of robust PI controllers for permanent magnet synchronous motors in terms of a linear matrix inequality based problem. A polytopic model of the plant is obtained and validated for the motor uncertain parameters belonging to intervals. The design procedure proposed here encompasses: i. suitable plant uncertainties inclusion and the use of practical design control constraints; ii. robust PI computation based on linear matrix inequalities with a very fast solution; iii. simulation analyses; and iv. experimental evaluations. The robust PI controller can produce superior speed regulation than a PI controller designed only for the nominal parameters, including better disturbance rejection and H-infinity performance. Experimental results confirm the viability of the proposal, which can be seen as an efficient alternative to trade off performance and robustness for PI controllers in this application233310319CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPES306197/2015-4não te

Interconnection and damping assignment passivity-based non-linear observer control for efficiency maximization of permanent magnet synchronous motor

The permanent magnet synchronous motor (PMSM) has several advantages over the DC motor and is gradually replacing it in the industry. The dynamics of the PMSM are described by non-linear equations; it is sensitive to unknown external disturbances (load), and its characteristics vary over time. All of these restrictions complicate the control task. Non-linear controls are required to adjust for non-linearities and the drawbacks mentioned above. This paper investigates an interconnection and damping assignment (IDA) passivity-based control (PBC) combined with a non-linear observer approach for the PMSM using the model represented in the dq-frame. The IDA-PBC approach has the inherent benefit of not canceling non-linear features but compensating them in a damped manner. The suggested PBC is in charge of creating the intended dynamic of the system, while the non-linear observer is in charge of reconstructing the recorded signals in order to compel the PMSM to track speed. The primary objective of this study is to synthesize the controller while accounting for the whole dynamic of the PMSM and making the system passive. It is performed by restructuring the energy of the proposed strategy and introducing a damping component that addresses the non-linear elements in a damped instead of deleted way, so providing a duality concept between both the IDA-PBC and the observer There are three methods for computing IDA-PBC: parametric, nonparametric, and algebraic. The parameterized IDA-PBC method is used to control the speed of the PMSM. This method uses the energy function in parameterized closed-loop in terms of some functions depending on the system’s state vector, such that the energy formation step is satisfied. Then, the original port-controlled Hamiltonian (PCH) dynamics in open-loop (OL) are equalized with the desired one in closed-loop (CL). The equalization process allows obtaining a set of solutions of the partial differential equations. The latter must be solved in terms of the parameters of the energy function of the closed-loop. Finally, the stability properties are studied using the Lyapunov theory. Generally, the proposed candidate offers high robustness, fast speed convergence, and high efficiency over the conventional benchmark strategies. The effectiveness of the proposed strategy is performed under extensive numerical investigation with MATLAB/Simulink software