scholarly journals Energy optimization of an electric car using losses minimization and intelligent predictive torque control

2020 ◽  
Vol 14 ◽  
pp. 174830262096669
Author(s):  
Habib Kraiem ◽  
Shaaban M Shaaban
Keyword(s):  
Electric Vehicles ◽  
Rotation Speed ◽  
Energy Optimization ◽  
Torque Control ◽  
Control Algorithms ◽  
Electric Car ◽  
Optimization Study ◽  
Pi Controllers ◽  
Stator Flux ◽  
Tuning Methods

Autonomy is considered an important criterion that characterizes the performance of electric vehicles. It is represented by the distance that could be traveled by a fully electric vehicle which mainly depends on several parameters such as the vehicle model, type of battery, type of motor, etc. In this context, to improve the autonomy of electric vehicles, this paper represents an optimization study for the electric motor based on two contributions. The first devise an energy optimization algorithm to reduce the motor losses by calculation of the stator flux reference according to the electromagnetic torque and the rotation speed. The second is concerned with controller parameters adjustment using the Particle Swarm Optimization (PSO) technique to improve the efficacy and robustness of the drive. The performance of this strategy is evaluated in terms of torque, flux ripples, and transient response to step variations of the torque control. A comparative study of the designed PI controllers based on PSO with four other control algorithms and tuning methods is established in order to prove the efficiency of PI_PSO. The analysis, modeling, and simulation results are presented to verify the validity of the proposed overall optimization study.

Electric Vehicle Improved by Three-Phase Asynchronous Cooled Motor

2013 ◽  
Author(s):  
Giuseppe Rattighieri ◽  
Michele Trancossi ◽  
Nicola Dorigo Salomon ◽  
Dean Vucinic
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
High Speed ◽  
Rotation Speed ◽  
Reggio Emilia ◽  
Heavy Load ◽  
Power Train ◽  
Electric Car ◽  
Three Phase ◽  
Cabin Interior

This paper presents the EVITA electric car. EVITA is the acronym of Electric Vehicle Improved by Three-phase Asynchronous cooled motor. It is a research project developed jointly by RGEngineering and University of Modena and Reggio Emilia. It aims to produce a novel electric power train with the capability of solving three fundamental problems of today commercial electric vehicles: 1. direct torque dependency of the rotation speed, and its reduction at high speed regimes; 2. electric motors performances reduction due to the overheating effects under heavy load conditions; 3. acclimatization of the car cabin interior in winter times.

Improved ANFIS based MRAC observer for sensorless control of PMSM

2021 ◽  
pp. 1-13
Author(s):  
Suryakant ◽  
Mini Sreejeth ◽  
Madhusudan Singh
Keyword(s):  
Fuzzy Inference ◽  
Permanent Magnet Synchronous Motor ◽  
Torque Control ◽  
Control Algorithms ◽  
Motor Speed ◽  
Inference System ◽  
Rotor Position ◽  
Improved Performance ◽  
Incremental Encoder ◽  
Model Reference Adaptive

Detection of the rotor position is an important prerequisite for controlling the speed and developed torque in permanent magnet synchronous motor (PMSM). Even though use of incremental encoder and resolver is one of the popular schemes for sensing the rotor position in a PMSM drive, it increases the size and weight of the drive and reduces its reliability. Dynamic modeling of the motor and control algorithms are often used in sensor-less control of PMSM to estimate rotor position and motor speed. Most sensor-less control algorithms use machine parameters like torque constant, stator inductances and stator resistance for estimating the rotor position and speed. However, with accuracy of such estimation and the performance of the motor degrades with variation in motor parameters. Model reference adaptive control (MRAC) provides a simple solution to this issue. An improved Adaptive neuro-fuzzy inference system (ANFIS) based MRAC observer for speed control of PMSM drive is presented in this paper. In the proposed method adaptive model and adaptive mechanism are replaced by an improved ANFIS controller, which neutralize the effect of parametric variation and results in improved performance of the drive. The modeling equations of PMSM are used to estimate the rotor position for speed and torque control of the drive. Simulation studies have been carried out under various operating condition using MATLAB/Simulink. In addition, a comparative analysis of the conventional MRAC based observer and improved ANFIS based MRAC observer is carried out. It is observed that the proposed method results in better performance of the PMSM drive.

scholarly journals Stability Control for Electric Vehicles with Four In-Wheel-Motors Based on Sideslip Angle

2021 ◽  
Vol 12 (1) ◽  
pp. 42
Author(s):  
Kun Yang ◽  
Danxiu Dong ◽  
Chao Ma ◽  
Zhaoxian Tian ◽  
Yile Chang ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Control Method ◽  
Sliding Mode ◽  
Stability Control ◽  
Torque Control ◽  
Wheel Load ◽  
Sideslip Angle ◽  
Distribution Method ◽  
Load Rate ◽  
The Stability

Tire longitudinal forces of electrics vehicle with four in-wheel-motors can be adjusted independently. This provides advantages for its stability control. In this paper, an electric vehicle with four in-wheel-motors is taken as the research object. Considering key factors such as vehicle velocity and road adhesion coefficient, the criterion of vehicle stability is studied, based on phase plane of sideslip angle and sideslip-angle rate. To solve the problem that the sideslip angle of vehicles is difficult to measure, an algorithm for estimating the sideslip angle based on extended Kalman filter is designed. The control method for vehicle yaw moment based on sliding-mode control and the distribution method for wheel driving/braking torque are proposed. The distribution method takes the minimum sum of the square for wheel load rate as the optimization objective. Based on Matlab/Simulink and Carsim, a cosimulation model for the stability control of electric vehicles with four in-wheel-motors is built. The accuracy of the proposed stability criterion, the algorithm for estimating the sideslip angle and the wheel torque control method are verified. The relevant research can provide some reference for the development of the stability control for electric vehicles with four in-wheel-motors.

scholarly journals Performance Improvement of Servo Control System Driven by Novel PMSM-DTC Based On Fixed Sector Division Criterion

Energies ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 2154 ◽  
Author(s):  
Dazhi Wang ◽  
Tianqing Yuan ◽  
Xingyu Wang ◽  
Xinghua Wang ◽  
Yongliang Ni
Keyword(s):  
Control System ◽  
Performance Improvement ◽  
Error Compensation ◽  
Permanent Magnet Synchronous Motor ◽  
Direct Torque Control ◽  
Torque Control ◽  
Servo Control ◽  
Flux Linkage ◽  
Servo Control System ◽  
Stator Flux

In order to improve the performance of the servo control system driven by a permanent magnet synchronous motor (PMSM) under novel direct torque control (NDTC), which, utilizing composite active vectors, fixed sector division criterion, is proposed in this paper. The precondition of the accurate compensations of torque and flux errors is that the sector where the stator flux linkage is located can be determined accurately. Consequently, the adaptive sector division criterion is adopted in NDTC. However, the computation burden is inevitably increased with the using of the adaptive part. On the other hand, the main errors can be compensated through SV-DTC (DTC-utilizing single active vector), while another active vector applied in NDTC can only supply the auxiliary error compensation. The relationships of the two active vectors’ characteristics in NDTC are analyzed in this paper based on the active factor. Furthermore, the fixed sector division criterion is proposed for NDTC (FS-NDTC), which can classify the complexity of the control system. Additionally, the switching table for the selections of the two active vectors is designed. The effectiveness of the proposed FS-NDTC is verified through the experimental results on a 100-W PMSM drive system.

scholarly journals A holistic review on advanced bi-directional EV charging control algorithms

2021 ◽  
Vol 1 (1) ◽  
pp. 78-88
Author(s):  
Xiaoying Tang ◽  
Chenxi Sun ◽  
Suzhi Bi ◽  
Shuoyao Wang ◽  
Angela Yingjun Zhang
Keyword(s):  
Electric Vehicles ◽  
Electricity Market ◽  
Control Algorithms ◽  
Future Research ◽  
Scheduling Problems ◽  
Time Data ◽  
Open Problems ◽  
Holistic Review ◽  
Charging Control ◽  
Ev Charging

The rapid growth of electric vehicles (EVs) has promised a next-generation transportation system with reduced carbon emission. The fast development of EVs and charging facilities is driving the evolution of Internet of Vehicles (IoV) to Internet of Electric Vehicles (IoEV). IoEV benefits from both smart grid and Internet of Things (IoT) technologies which provide advanced bi-directional charging services and real-time data processing capability, respectively. The major design challenges of the IoEV charging control lie in the randomness of charging events and the mobility of EVs. In this article, we present a holistic review on advanced bi-directional EV charging control algorithms. For Grid-to-Vehicle (G2V), we introduce the charging control problem in two scenarios: 1) Operation of a single charging station and 2) Operation of multiple charging stations in coupled transportation and power networks. For Vehicle-to-Grid (V2G), we discuss how EVs can perform energy trading in the electricity market and provide ancillary services to the power grid. Besides, a case study is provided to illustrate the economic benefit of the joint optimization of routing and charging scheduling of multiple EVs in the IoEV. Last but not the least, we will highlight some open problems and future research directions of charging scheduling problems for IoEVs.

scholarly journals A New Optimal DTC Switching Strategy for Open-End Windings Induction Machine using Dual Inverter

2021 ◽  
Vol 12 (3) ◽  
pp. 1405
Author(s):  
Nabilah Aisyah ◽  
Maaspaliza Azri ◽  
Auzani Jidin ◽  
M. Z. Aihsan ◽  
MHN Talib
Keyword(s):  
Dynamic Response ◽  
High Speed ◽  
Dynamic Condition ◽  
Dynamic Control ◽  
Direct Torque Control ◽  
Torque Control ◽  
Dynamic Responses ◽  
Voltage Source ◽  
Optimal Switching ◽  
Stator Flux

<span>Since the early 1980s, fast torque dynamic control has been a subject of research in AC drives. To achieve superior torque dynamic control, two major techniques are used, namely Field Oriented Control (FOC) and Direct Torque Control (DTC), spurred on by rapid advances in embedded computing systems. Both approaches employ the space vector modulation (SVM) technique to perform the voltage source inverter into over modulation region for producing the fastest torque dynamic response. However, the motor current tends to increase beyond its limit (which can damage the power switches) during the torque dynamic condition, due to inappropriate flux level (i.e. at rated stator flux). Moreover, the torque dynamic response will be slower, particularly at high speed operations since the increase of stator flux will produce negative torque slopes more often. The proposed research aims to formulate an optimal switching modulator and produce the fastest torque dynamic response. In formulating the optimal switching modulator, the effects of selecting different voltage vectors on torque dynamic responses will be investigated. With greater number of voltage vectors offered in dual inverters, the identification of the most optimal voltage vectors for producing the fastest torque dynamic responses will be carried out based on the investigation. The main benefit of the proposed strategy is that it provides superior fast torque dynamic response which is the main requirements for many AC drive applications, e.g. traction drives, electric transportations and vehicles.</span>

Sign in / Sign up

Export Citation Format

Share Document