Estimation of Battery Soc for Hybrid Electric Vehicle using Coulomb Counting Method

2018 ◽  
Vol 19 (2) ◽  
Author(s):  
Bachir Zine ◽  
Khoudir Marouani ◽  
Mohamed Becherif ◽  
Said Yahmedi
Keyword(s):  
Electric Vehicle ◽  
Electric Charge ◽  
Hybrid Electric Vehicle ◽  
State Of Charge ◽  
Experimental Results ◽  
Generic Model ◽  
Battery Electric Vehicle ◽  
Counting Method ◽  
Soc Estimation ◽  
Battery State Of Charge

Abstract:The autonomy of the Battery Electric Vehicle is a key point in the development and commercialization of this kind of vehicle. The requested autonomy is directly linked to the amount of the stored and remaining energy in the battery which is the State of Charge (SOC).This paper presents battery state of charge (SOC) estimation using coulomb counting method. So, the quantity of electric charge is calculated during the battery cycle of charge and discharge and compared to the estimated value based on the battery generic model. Also, experimental results are carried out in order to validate this study.

scholarly journals An Investigation of Battery Electric Vehicle Driving and Charging Behaviors Using Vehicle Usage Data Collected in Shanghai, China

2018 ◽  
Vol 2672 (24) ◽  
pp. 20-30 ◽  
Author(s):  
Jie Yang ◽  
Jing Dong ◽  
Qi Zhang ◽  
Zhiyuan Liu ◽  
Wei Wang
Keyword(s):  
Electric Vehicle ◽  
Time Of Day ◽  
State Of Charge ◽  
Learning Approach ◽  
Battery Electric Vehicle ◽  
Summary Statistics ◽  
Start Time ◽  
Machine Learning Approach ◽  
Before And After ◽  
Battery State Of Charge

This paper investigates the driving and charging behaviors of battery electric vehicle (BEV) drivers observed in Shanghai, China. The summary statistics are compared with the observations from the U.S. EV Project. A machine-learning approach, namely self-organizing feature map (SOM), is adopted as a classifier to analyze BEV drivers’ habitual behaviors. The inter-driver heterogeneities are examined in terms of: the distributions of distance traveled per day, the start time of charging, the number of charges per day, distance traveled between consecutive charges, battery state of charge (SOC) before and after charging, and time-of-day electricity demand. It is found that ( a) BEV drivers demonstrate conservative charging behaviors, leading to short distances between consecutive charging events; ( b) a significant number of BEV drivers in Shanghai charge during daytime; ( c) the distributions depicting the driving and charging patterns vary greatly due to the diversity in travel activities among different drivers.

Online State of Charge Estimation for Battery of Electric Vehicle Using Sigma-Points Kalman Filters

2013 ◽  
Vol 427-429 ◽  
pp. 824-829
Author(s):  
Li Cun Fang ◽  
Gang Xu ◽  
Tian Li Li ◽  
Ke Min Zhu
Keyword(s):  
Electric Vehicle ◽  
Kalman Filters ◽  
Hybrid Electric Vehicle ◽  
Lithium Battery ◽  
Cell Model ◽  
Operating Conditions ◽  
State Of Charge ◽  
Battery Cell ◽  
Soc Estimation ◽  
Simulation And Experiment

An accurate state-of-charge (SOC) estimation of the hybrid electric vehicle (HEV) and electric vehicle (EV) battery pack is a difficult task to be performed online in a vehicle because of the noisy and low accurate measurements and the wide operating conditions in which the vehicle battery can operate. A Sigma-points Kalman Filters (SPKF) algorithm based on an improved Lithium battery cell model to estimate the SOC of a Lithium battery cell is proposed in this paper. The simulation and experiment results show the effectiveness and ease of implementation of the proposed technique.

scholarly journals Battery state of charge management strategies for a real-time controller of a Plug-in Hybrid Electric Vehicle

2018 ◽  
Vol 148 ◽  
pp. 258-265 ◽  
Author(s):  
Gabriele Caramia ◽  
Nicolò Cavina ◽  
Michele Caggiano ◽  
Stefano Patassa ◽  
Davide Moro
Keyword(s):  
Real Time ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Management Strategies ◽  
State Of Charge ◽  
Battery State Of Charge ◽  
Charge Management ◽  
Hybrid Electric

Hardware-in-the-loop simulation of regenerative braking for a hybrid electric vehicle

2002 ◽  
Vol 216 (11) ◽  
pp. 855-864 ◽  
Author(s):  
H Yeo ◽  
H Kim
Keyword(s):  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Continuous Variable ◽  
State Of Charge ◽  
Regenerative Braking ◽  
Vehicle Speed ◽  
Hardware In The Loop ◽  
Battery State Of Charge ◽  
Hybrid Electric

A regenerative braking algorithm and a hydraulic module are proposed for a parallel hybrid electric vehicle (HEV) equipped with a continuous variable transmission (CVT). The regenerative algorithm is developed by considering the battery state of charge, vehicle velocity and motor capacity. The hydraulic module consists of a reducing valve and a power unit to supply the front wheel brake pressure according to the control algorithm. In addition, a stroke simulator is designed to provide a similar pedal operation feeling. In order to evaluate the performance of the regenerative braking algorithm and the hydraulic module, a hardware-in-the-loop simulation (HILS) is performed. In the HILS system, the brake system consists of four wheel brakes and the hydraulic module. Dynamic characteristics of the HEV are simulated using an HEV simulator. In the HEV simulator, each element of the HEV powertrain such as internal combustion engine, motor, battery and CVT is modelled using MATLAB SIMULINK. In the HILS, a driver operates the brake pedal with his or her foot while the vehicle speed is displayed on the monitor in real time. It is found from the HILS that the regenerative braking algorithm and the hydraulic module suggested in this paper provide a satisfactory braking performance in tracking the driving schedule and maintaining the battery state of charge.

Electric Vehicle Battery SOC Estimation Based on EKF

2014 ◽  
Vol 926-930 ◽  
pp. 927-931 ◽  
Author(s):  
Hui Bao ◽  
Wei Jiang ◽  
Dan Wei
Keyword(s):  
Electric Vehicle ◽  
Good Accuracy ◽  
State Of Charge ◽  
Model Parameters ◽  
Static Characteristics ◽  
Soc Estimation ◽  
Mathematical Relation ◽  
Battery State Of Charge ◽  
Electric Vehicle Battery ◽  
Simulation Results

In order to estimate the battery state of charge (SOC) accurately, an improved Thevenin model of a battery is established, its mathematical relation is very simple, and also it is easy to realize. In addition, we identify the model parameters, and then use extended Calman filter algorithm to estimate the battery state of charge. The simulation results show that, this model can well reflect the dynamic and static characteristics of a battery, and the Calman algorithm can keep good accuracy in the estimation process.

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