A hybrid battery model and state of health estimation method for lithium-ion batteries

Sarıkurt, Türev; Ceylan, Murat; Balıkçı, Abdulkadir

doi:10.1109/energycon.2014.6850598

Cited by 8 publications

(6 citation statements)

References 28 publications

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“…The derivation of a battery mathematical model constitutes a complex task due to the complicated structure of a battery, as well as its nonlinear characteristics. Distinct battery models are utilized, such as electrochemical models, which take into consideration the internal processes within the cell, or statistical methods that derive model parameters using collected sampled data [7,8,9]. It is common practice to combine modeling methods, in order to obtain more accurate and robust models [7].…”

Section: A Brief Introductionmentioning

confidence: 99%

“…Considerable research efforts are focused on the topic of developing models for lithium polymer (LiPo) battery discharge and life cycles [7]. Generally, these models include autonomous batteries, in controlled environments (e.g.…”

Section: A Brief Introductionmentioning

confidence: 99%

“…Distinct battery models are utilized, such as electrochemical models, which take into consideration the internal processes within the cell, or statistical methods that derive model parameters using collected sampled data [7,8,9]. It is common practice to combine modeling methods, in order to obtain more accurate and robust models [7]. In addition, a majority of research is focused on the design of battery management systems (BMS), which are crucial to the needs of UAS powered by sources such as LiPo batteries.…”

Section: A Brief Introductionmentioning

confidence: 99%

“…These issues need to be considered when operating battery powered unmanned air systems. Currently, lithium-based battery characteristics offer the best power supply for small UAS' where reliability and weight power density are of importance [6].Considerable research efforts are focused on the topic of developing models for lithium polymer (LiPo) battery discharge and life cycles [7]. Generally, these models include autonomous batteries, in controlled environments (e.g.…”

mentioning

confidence: 99%

“…Generally, these models include autonomous batteries, in controlled environments (e.g. bench testers), as well as models specifically derived for the usage of battery packs in vehicles with variable power requirements [7]. The derivation of a battery mathematical model constitutes a complex task due to the complicated structure of a battery, as well as its nonlinear characteristics.…”

mentioning

confidence: 99%

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LiPo battery energy studies for improved flight performance of unmanned aerial systems

et al. 2016

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Energy storage is one of the most important determinants of how long and far a small electric powered unmanned aerial system (UAS) can fly. For years, most hobby and experimentalists used heavy fuels to power small drone-like systems. Electric motors and battery storage prior to the turn of the century were either too heavy or too inefficient for flight times of any usable duration. However, with the availability of brushless electric motors and lithium-based batteries everything has changed. Systems like the Dragon Eye, Pointer, and Raven are in service performing reconnaissance, intelligence, surveillance, and target acquisition (RISTA) for more than an hour at a time. More recently, multi-rotor vehicles have expanded small UAS capabilities to include activities with hovering and persistent surveillance. Moreover, these systems coupled with the surge of small, low-cost electronics can perform autonomous and semi-autonomous missions not possible just ten years ago. This paper addresses flight time limitation issues by proposing an experimental method with procedures for system identification that may lead to modeling of energy storage in electric UAS'. Consequently, this will allow for energy storage to be used more effectively in planning autonomous missions. To achieve this, a set of baseline experiments were designed to measure the energy consumption of a mid-size UAS multi-rotor. Several different flight maneuvers were considered to include different lateral velocities, climbing, and hovering. Therefore, the goal of this paper is to create baseline flight data for each maneuver to be characterized with a certain rate of energy usage. Experimental results demonstrate the feasibility and robustness of the proposed approach. Future work will include the development of mission planning algorithms that provide realistic estimates of possible mission flight times and distances given specific mission parameters.Keywords: Battery energy management, flight performance, modeling, unmanned aerial system A BRIEF INTRODUCTIONLithium-based batteries present advantageous characteristics, such as high charge and discharge rates, longevity, high energy density, and affordable cost accompanied with a lightweight structure [1,2,3,4]. Nonetheless, only small improvements in lithium-based batteries have occurred over the past ten years with the biggest improvement being the reduction of price. Even with the most advanced lithium-based batteries, electric multi-rotor UAS mission plans are often dictated by the flight time (and consequently path) of the vehicle [5]. In most scenarios, this is generally limited to approximately thirty minutes before battery protection measures activate and the craft must land. However, lithium-based batteries are still affected by charge and discharge rates, life cycles, temperature, and their capacity rating [1]. These issues need to be considered when operating battery powered unmanned air systems. Currently, lithium-based battery characteristics offer the best power supply for small UAS' where r...

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