State of Charge Management for Plug-In Hybrid Vehicles With Uncertain Trip Information

2015 ◽  
Vol 137 (9) ◽  
Author(s):  
Chris Manzie ◽  
Prakash Dewangan ◽  
Gilles Corde ◽  
Olivier Grondin ◽  
Antonio Sciarretta
Keyword(s):  
Hybrid Electric Vehicles ◽  
Management Strategies ◽  
Hybrid Vehicles ◽  
The State ◽  
State Of Charge ◽  
Environmental Benefits ◽  
Contributing Factors ◽  
Vehicle Velocity ◽  
Charge Management ◽  
A Charge

Efficient state of charge management of plug-in hybrid electric vehicles (PHEVs) differs from their nonplug-in counterparts through the utilization of a charge depleting (CD) mode of operation. Several studies have shown that a blended mode of CD holds fuel economy advantages over a CD and charge sustaining (CS) combination, however, these approaches assume knowledge of the total journey distance. Here, this assumption is relaxed and the state of charge trajectory was recalculated online using a weaker assumption that only a probability distribution accumulated over past trips is available. The importance of other contributing factors to the state of charge profile such as vehicle velocity and altitude is also assessed. Simulation results on a prototype plug-in hybrid are presented with an adaptive equivalent consumption minimization strategy (ECMS) used by the powertrain management to track the proposed state of charge trajectory. The financial and environmental benefits of the proposed approach relative to other state of charge management strategies are then calculated over a number of different cycles and conditions.

A Dynamic Programming Control Strategy for HEV

2012 ◽  
Vol 263-266 ◽  
pp. 541-544 ◽  
Author(s):  
Babici Leandru Corneliu Cezar ◽  
Onea Alexandru
Keyword(s):  
Dynamic Programming ◽  
Electric Vehicles ◽  
Control Strategy ◽  
Hybrid Electric Vehicles ◽  
The State ◽  
State Of Charge ◽  
Battery Pack ◽  
Matlab Simulink ◽  
Hybrid Electric

Dynamic programming is a very powerful algorithmic paradigm which solves a problem by identifying subproblems and tackling them one by one. First the smallest are solved, and then using their answers, it can be figured out larger ones, until the whole lot of them is solved. This paper presents a control strategy for hybrid electric vehicles, based on the dynamic programming, applied in MATLAB, Simulink environment, using ADVISOR. It was tried this method due to the calculation speed of the suitable torque and speed required from the engine, considering the driver power request (torque and speed), and the state of charge (SOC) of the batteries. Using the fuel converter (FC) fuel map, and the remaining SOC of the battery pack, it was designed an algorithm that will chose at each time the required torque and speed from the first and second source of power.

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

Optimized operation of large scale battery systems

2022 ◽  
Vol 70 (1) ◽  
pp. 67-78
Author(s):  
Daniel Lehmann ◽  
Diego Hidalgo Rodriguez ◽  
Michel Brack
Keyword(s):  
Large Scale ◽  
Mathematical Optimization ◽  
The State ◽  
State Of Charge ◽  
Operational Experience ◽  
Primary Control ◽  
Battery System ◽  
Operational Costs ◽  
Battery Systems ◽  
Charge Management

Abstract In the decentralized renewable driven electric energy system, economically viable battery systems become increasingly important for providing grid-related services. End of 2016, STEAG has successfully started the commercial operation of six 15 MW large scale battery systems which have been incorporated in STEAG’s primary control pool. During the commissioning phase, extensive effort has been spent in optimizing the operational efficiency of these systems with promising results. However, the operation experience has shown that there is still significant potential for improving the system behavior as well as reducing the aging of the battery cells. By analyzing historical data of the charging power associated with the state of charge management, opportunities for significantly reducing the operational costs have been identified. By means of more involved model-based control strategies, which adequately consider the specific characteristics of the battery system, and by using mathematical optimization and artificial intelligence, adapting the state of charge management strategy to new applications, these additional cost savings can be obtained. Apart from giving insights into the operational experience with large scale battery systems, the contribution of this paper lies in proposing strategies for reducing the operational costs of the battery system using classical approaches as well as mathematical optimization and neural networks. These approaches will be illustrated by simulation results.

Effects of Using an Electrically Heated Catalyst on the State of Charge of the Battery Pack for Series Hybrid Electric Vehicles at Cold Start

2020 ◽  
Author(s):  
Suchitra Sivakumar ◽  
Hajime Shingyouchi ◽  
Xieyang Yan ◽  
Toshinori Okajima ◽  
Kyohei Yamaguchi ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Cold Start ◽  
The State ◽  
State Of Charge ◽  
Battery Pack ◽  
Hybrid Electric

scholarly journals The Role of Supercapacitors in Regenerative Braking Systems

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2683 ◽  
Author(s):  
Julius Partridge ◽  
Dina Ibrahim Abouelamaimen
Keyword(s):  
Discharge Rate ◽  
Storage System ◽  
Energy Storage System ◽  
The State ◽  
State Of Charge ◽  
Regenerative Braking ◽  
Braking System ◽  
Charge Rate ◽  
Charging Current ◽  
A Charge

A supercapacitor module was used as the energy storage system in a regenerative braking test rig to explore the opportunities and challenges of implementing supercapacitors for regenerative braking in an electric drivetrain. Supercapacitors are considered due to their excellent power density and cycling characteristics; however, the performance under regenerative braking conditions has not been well explored. Initially the characteristics of the supercapacitor module were tested, it is well known that the capacitance of a supercapacitor is highly dependent on the charge/discharge rate with a drop of up to 9% found here between the rated capacitance and the calculated value at a 100 A charge rate. It was found that the drop in capacitance was significantly reduced when a variable charge rate, representative of a regenerative braking test, was applied. It was also found that although supercapacitors have high power absorbing characteristics, the state-of-charge significantly impacts on the charging current and the power absorbing capacity of a supercapacitor-based regenerative braking system. This owed primarily to the current carrying capacity of the power electronic converters required to control the charge and discharge of the supercapacitor module and was found to be a fundamental limitation to the utilisation of supercapacitors in a regenerative braking system. In the worst cases this was found to impact upon the ability of the motor to apply the desired braking torque. Over the course of the tests carried out the overall efficiency was found to be up to 68%; however, the main source of loss was the motor. It was found that measurement of the state-of-charge using the rated capacitance significantly over-estimates the efficiency of the system.

scholarly journals A Review of Optimal Energy Management Strategies for Hybrid Electric Vehicle

2014 ◽  
Vol 2014 ◽  
pp. 1-19 ◽  
Author(s):  
Aishwarya Panday ◽  
Hari Om Bansal
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Fuel Economy ◽  
Hybrid Electric Vehicles ◽  
Control Strategies ◽  
Management Strategies ◽  
Energy Optimization ◽  
Hybrid Vehicles ◽  
Power Split ◽  
Hybrid Electric

Presence of an alternative energy source along with the Internal Combustion Engine (ICE) in Hybrid Electric Vehicles (HEVs) appeals for optimal power split between them for minimum fuel consumption and maximum power utilization. Hence HEVs provide better fuel economy compared to ICE based vehicles/conventional vehicle. Energy management strategies are the algorithms that decide the power split between engine and motor in order to improve the fuel economy and optimize the performance of HEVs. This paper describes various energy management strategies available in the literature. A lot of research work has been conducted for energy optimization and the same is extended for Plug-in Hybrid Electric Vehicles (PHEVs). This paper concentrates on the battery powered hybrid vehicles. Numerous methods are introduced in the literature and based on these, several control strategies are proposed. These control strategies are summarized here in a coherent framework. This paper will serve as a ready reference for the researchers working in the area of energy optimization of hybrid vehicles.

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