Optimal configuration planning of rule and optimization-based driven storage coupled micro cogeneration systems by the implementation of constraint programming

Mohammadi, Hesam; Mohammadi, Mohammad; Ghasemi, Amir

doi:10.1016/j.est.2021.103934

Cited by 13 publications

(2 citation statements)

References 74 publications

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“…Currently, SOC estimation methods can be divided into three categories: direct measurement method, [ 9 ] data‐driven method, [ 10 ] and model‐driven method. [ 11,12 ] The Ampere hour (AH) method estimates SOC by integrating the charge/discharge current, but it relies on accurate initial SOC information and is susceptible to error accumulation.…”

Section: Introductionmentioning

confidence: 99%

State of Charge Estimation for Lithium‑Ion Batteries Based on Extended Kalman Particle Filter and Orthogonal Optimized Battery Model

Shi,

Zhang,

et al. 2024

Advcd Theory and Sims

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State of charge (SOC) is a key state variable in lithium‑ion battery management system. The battery model and estimation algorithm are important factors that affect the accuracy of SOC estimation. In this paper, the optimization battery model is created by optimizing the hybrid power pulse characteristic (HPPC) parameter combination through orthogonal analysis. The simulation results demonstrate that optimizing the HPPC parameter combinations can improve battery modeling accuracy. Then, an extended Kalman particle filter (EKPF) algorithm is proposed by using the extended Kalman filter (EKF) algorithm as the density function of the particle filter (PF) algorithm. The EKPF algorithm is verified under the dynamic stress test and Beijing bus dynamic stress test conditions, the root mean absolute errors and root mean square errors in all cases are less than 1.5%. The experimental results show that the EKPF algorithm can combine the advantages of EKF and PF to estimate lithium‐ion battery SOC accurately.

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Section: Introductionmentioning

confidence: 99%

State of Charge Estimation for Lithium‑Ion Batteries Based on Extended Kalman Particle Filter and Orthogonal Optimized Battery Model

Shi,

Zhang,

et al. 2024

Advcd Theory and Sims

View full text Add to dashboard Cite

show abstract

“…According to international agreements, achieving neutral-carbon emissions is one of the ideas for sustainable development in today's societies [ 9 , 10 ]. However, over 80% of the society's energy requirements are met through fossil fuel-burned power plants, which results in a huge amount of carbon being released into the atmosphere [ 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

Cost and environmental analysis and optimization of a new and green three-level waste heat recovery-based cogeneration cycle: A comparative study

Nikafshan Rad,

Ghasemi,

Marefati

2024

Heliyon

Self Cite

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A comprehensive investigation of a water and energy-based waste integrated system: Techno-eco-environmental-sustainability aspects

et al. 2023

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Optimal configuration planning of rule and optimization-based driven storage coupled micro cogeneration systems by the implementation of constraint programming

Cited by 13 publications

References 74 publications

State of Charge Estimation for Lithium‑Ion Batteries Based on Extended Kalman Particle Filter and Orthogonal Optimized Battery Model

State of Charge Estimation for Lithium‑Ion Batteries Based on Extended Kalman Particle Filter and Orthogonal Optimized Battery Model

Cost and environmental analysis and optimization of a new and green three-level waste heat recovery-based cogeneration cycle: A comparative study

A comprehensive investigation of a water and energy-based waste integrated system: Techno-eco-environmental-sustainability aspects

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