scholarly journals Thermoelectric Modeling and Online SOC Estimation of Li-Ion Battery for Plug-In Hybrid Electric Vehicles

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Aishwarya Panday ◽  
Hari Om Bansal ◽  
Pramod Srinivasan
Keyword(s):  
Electric Vehicles ◽  
Energy Demand ◽  
Hybrid Electric Vehicles ◽  
Environmental Concern ◽  
Open Circuit ◽  
Li Ion Battery ◽  
Vehicle Performance ◽  
Li Ion ◽  
Hybrid Electric ◽  
Thermoelectric Model

The increasing oil price, energy demand, and environmental concern are leading to a global switch towards Plug-In Hybrid Electric Vehicles (PHEVs). In a PHEV, Li-ion battery is considered as the primary propelling source. Therefore, an accurate battery model is required to predict theI-Vcharacteristic and dynamic behavior of a battery. This paper presents a highly effective thermoelectric model of Li-ion battery developed in Simulink. An algorithm is proposed for estimation of state of charge (SOC) and open circuit voltage (OCV) adaptively to notify the exact SOC level for better utilization of battery power and optimal vehicle performance. Thermal behavior of Li-ion battery is investigated for wide temperature range and its effect on resistance, capacity, and OCV is recorded. The minimum SOC level to which battery can get depleted is calculated using gradient method. The proposed simulation results are analyzed with those of earlier models and found to be better.

scholarly journals Li-Ion Battery Performance Degradation Modeling for the Optimal Design and Energy Management of Electrified Propulsion Systems

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1629 ◽  
Author(s):  
Li Chen ◽  
Yuqi Tong ◽  
Zuomin Dong
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Performance Degradation ◽  
Power Demand ◽  
Li Ion Battery ◽  
Propulsion Systems ◽  
Degradation Model ◽  
Li Ion ◽  
Hybrid Electric

Heavy-duty hybrid electric vehicles and marine vessels need a sizeable electric energy storage system (ESS). The size and energy management strategy (EMS) of the ESS affects the system performance, cost, emissions, and safety. Traditional power-demand-based and fuel-economy-driven ESS sizing and energy management has often led to shortened battery cycle life and higher replacement costs. To consider minimizing the total lifecycle cost (LCC) of hybrid electric propulsion systems, the battery performance degradation and the life prediction model is a critical element in the optimal design process. In this work, a new Li-ion battery (LIB) performance degradation model is introduced based on a large set of cycling experiment data on LiFePO4 (LFP) batteries to predict their capacity decay, resistance increase and the remaining cycle life under various use patterns. Critical parameters of the semi-empirical, amended equivalent circuit model were identified using least-square fitting. The model is used to calculate the investment, operation, replacement and recycling costs of the battery ESS over its lifetime. Validation of the model is made using battery cycling experimental data. The new LFP battery performance degradation model is used in optimizing the sizes of the key hybrid electric powertrain component of an electrified ferry ship with the minimum overall LCC. The optimization result presents a 12 percent improvement over the traditional power demand-driven hybrid powertrain design method. The research supports optimal sizing and EMS development of hybrid electric vehicles and vessels to achieve minimum lifecycle costs.

A Separated-Frequency Parameters Identification Method of Li-Ion Battery Model for Electric Vehicles

2014 ◽  
Vol 672-674 ◽  
pp. 727-730 ◽  
Author(s):  
Da Zhong Mu ◽  
Zhi Hong Dong ◽  
Ming Fei Wang
Keyword(s):  
Electric Vehicles ◽  
Main Idea ◽  
Open Circuit ◽  
Current Data ◽  
Model Parameters ◽  
Wavelet Domain ◽  
Li Ion Battery ◽  
Battery Model ◽  
Identification Method ◽  
Li Ion

This paper proposed a separated-frequency identification method of Li-ion battery model for Electric Vehicles (EVs). The main idea is to decompose the measured terminal voltage and current data in wavelet domain, and then the weighting least squares (LS) algorithm is used to extract the model parameters. Since the signal energy of open circuit voltage (OCV) mainly distributes in the low frequency band, the identifiable wavelet-domain battery model can be approximately obtained by neglecting the high frequency wavelet decomposition coefficients. Furthermore, based on the Akaike’s information criterion, we study the optimum decomposition order of the wavelet-domain battery model.

Design of coordinated control strategy during driving mode switching for parallel hybrid electric vehicles

2018 ◽  
Vol 41 (9) ◽  
pp. 2507-2520
Author(s):  
Jiangtao Fu ◽  
Shuzhong Song ◽  
Zhumu Fu ◽  
Jianwei Ma
Keyword(s):  
Electric Vehicles ◽  
Control Strategy ◽  
Hybrid Electric Vehicles ◽  
Combustion Engine ◽  
Coordinated Control ◽  
Mode Switching ◽  
Vehicle Performance ◽  
Driving Mode ◽  
Response Characteristics ◽  
Hybrid Electric

Hybrid electric vehicles (HEVs) require the power to drive the vehicle via a combination of internal combustion engine (ICE) and electric machine (EM). To improve the drivability, the smooth torque change during the driving mode switching is essential. This task can be achieved by using the coordinated control strategy. This paper presents a coordinated control strategy based on considering the different dynamic response characteristics of the ICE and the EM, which can effectively suppress the torque surge during the driving mode switching processes. The novelty lies in the proposed control is a motor active synchronization control strategy without clutch disengagement based on the mode switching classification. The coordinated control strategy is designed according to the classification of the driving modes. The objective is to minimize torque fluctuation and maintain or improve the driving performance of the vehicle. Results from the computer simulation demonstrate the effectiveness of this approach in reducing the torque surge without sacrificing vehicle performance.

An Overview of Electric Vehicle Technology

2017 ◽  
pp. 198-220 ◽  
Author(s):  
Nadia Adnan ◽  
Shahrina Md Nordin ◽  
Imran Rahman ◽  
Pandian Vasant ◽  
Muhammad Amir Noor
Keyword(s):  
Electric Vehicles ◽  
Power Plants ◽  
Hybrid Electric Vehicles ◽  
Environmental Concern ◽  
Policy Option ◽  
Green Technologies ◽  
Transportation Sector ◽  
Conventional Technology ◽  
Hybrid Electric ◽  
Market Diffusion

Modern studies on green technologies for transportation sector are attaining attraction among the research communities from diverse parts. We learn the significance of plug-in hybrid electric vehicles which play a key role toward the policy option to reduce the environmental concern. There are major uncertainties in the diffusion of electric vehicles timing of market diffusion among consumers. However, there has been a considerable effort made towards the benefit of electric vehicles demand. Yet, the debates on consumer behavior towards the adoption of electric vehicles are less recognized. Researcher's highlighting the significance of plug-in hybrid electric vehicles from a combined perspective considering V2G technology which allows bi-directional flow of electricity. On the other hand, when electric vehicles are recharged from electricity produced from conventional technology power plants such as oil or coal-fired plants, they may produce equal or sometimes more greenhouse gas emissions than conventional gasoline vehicles.

Sign in / Sign up

Export Citation Format

Share Document