A hybrid model predictive and fuzzy logic based control method for state of power estimation of series-connected Lithium-ion batteries in HEVs

Esfandyari, Mohammad Javad; Yazdi, Mohammad Reza Hairi; Esfahanian, Vahid; Masih‐Tehrani, Masoud; Nehzati, Hassan; Shekoofa, Omid

doi:10.1016/j.est.2019.100758

Cited by 48 publications

(15 citation statements)

References 39 publications

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“…Furthermore, the payback period is nine months 27 days besides that reduction of fuel consumption is 28.61%. It is highly recommended for those who want to study in this context as long as they use a sophisticated controller (such as developed in Esfandyari et al, 2019;Masih-Tehrani et al, 2019) to control the flywheel and engine simultaneously, in order to get the engine (Salavati-Zadeh et al, 2016;Ghavami et al, 2018) working conditions at optimal points in all the time of cycle travel. Another suggestion is that the combination flywheel hybrid with other available hybrids such as supercapacitor and battery (Masih-Tehrani and Dahmardeh, 2018;Rahimirad et al, 2019) to improve storage performance, in order to use it for working in extra time.…”

Section: Discussionmentioning

confidence: 99%

Design and energy optimisation of a hybrid flywheel bus rapid transit

Ghajarloo

Masih‐Tehrani

Kheybari

2020

IJHM

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A hybrid flywheel powertrain system for a bus rapid transit (BRT) is designed in this paper, using a technical-economic study. The modern high-speed flywheel, which is used in the modern heavy vehicle hybrid powertrain, has high efficiency, low weight, and low initial cost. In contrary to the other powertrain hybridisation options, the energy conversion does not need using the flywheel energy storage system. Therefore, the power charge and discharge process are high-speed and efficient. The economic study is defined based on component price and fuel consumption cost. The model of the conventional and the hybrid bus is generated in AVL CRUISE software. Results show that the hybrid flywheel bus has better efficiency in BRT driving cycle in comparison with the normal Tehran City bus driving cycle. The optimal flywheel capacity is 1.4 MJ to use in Tehran BRT, which has ten months payback period. The reduction in fuel consumption is 28.61%.

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Section: Discussionmentioning

confidence: 99%

Design and energy optimisation of a hybrid flywheel bus rapid transit

Ghajarloo

Masih‐Tehrani

Kheybari

2020

IJHM

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“…47 Furthermore, fuzzy logic has been used in parameter identification for LIB. 48 In our case, the identification is based on the RLS method, which shows exponential convergence when the existing noise is white and centered with persistent excitation. 49 Since we have chosen the RLS method, sampling time is one of the parameters that can improve the convergence.…”

Section: Identification Of Equivalent Circuit Parametersmentioning

confidence: 99%

Adaptive sliding mode estimation of state of charge implemented on a field programmable gate array Spartan‐6 Xilinx device

2021

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This paper presents the implementation of adaptive sliding mode estimation (ASME) of the state of charge of a battery on a field programmable gate array (FPGA). The study is conducted in two steps: in the first step, we design an adaptive sliding mode observer by taking into account an electrical equivalent circuit describing the battery's behavior and identify the parameters of this equivalent circuit by using the recursive least squares estimation method. In the second step, we study the implementation of this ASME on an FPGA card.

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“…Fuzzy logic control theory can be also applied in SOP estimation. In [63,64], a fuzzy logic controller is designed to prevent batteries from breaching the pre-set constraints and guarantee the safe operation of lithium-ion batteries. SOP estimation outcomes, provided by a MPC algorithm at CC or CCCV modes, will be delivered to a fuzzy logic controller, which divides the safe operating area into an inner and outer region.…”

Section: Optimisation Control-based Sop Estimationmentioning

confidence: 99%

A Review of Equivalent Circuit Model Based Online State of Power Estimation for Lithium-Ion Batteries in Electric Vehicles

Guo

Shen

2021

Vehicles

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With rapid transportation electrification worldwide, lithium-ion batteries have gained much attention for energy storage in electric vehicles (EVs). State of power (SOP) is one of the key states of lithium-ion batteries for EVs to optimise power flow, thereby requiring accurate online estimation. Equivalent circuit model (ECM)-based methods are considered as the mainstream technique for online SOP estimation. They primarily vary in their basic principle, technical contribution, and validation approach, which have not been systematically reviewed. This paper provides an overview of the improvements on ECM-based online SOP estimation methods in the past decade. Firstly, online SOP estimation methods are briefed, in terms of different operation modes, and their main pros and cons are also analysed accordingly. Secondly, technical contributions are reviewed from three aspects: battery modelling, online parameters identification, and SOP estimation. Thirdly, SOP testing methods are discussed, according to their accuracy and efficiency. Finally, the challenges and outlooks are presented to inspire researchers in this field for further developments in the future.

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A hybrid model predictive and fuzzy logic based control method for state of power estimation of series-connected Lithium-ion batteries in HEVs

Cited by 48 publications

References 39 publications

Design and energy optimisation of a hybrid flywheel bus rapid transit

Design and energy optimisation of a hybrid flywheel bus rapid transit

Adaptive sliding mode estimation of state of charge implemented on a field programmable gate array Spartan‐6 Xilinx device

A Review of Equivalent Circuit Model Based Online State of Power Estimation for Lithium-Ion Batteries in Electric Vehicles

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