Identifiability and parameter estimation of the single particle lithium-ion battery model

This paper investigates the identifiability and estimation of the parameters of the single particle model (SPM) for lithium-ion battery simulation. Identifiability is addressed both in principle and in practice. The approach begins by grouping parameters and partially non-dimensionalising the SPM to determine the maximum expected degrees of freedom in the problem. We discover that, excluding open circuit voltage, there are only six independent parameters. We then examine the structural identifiability by considering whether the transfer function of the linearised SPM is unique. It is found that the model is unique provided that the electrode open circuit voltage functions have a known non-zero gradient, the parameters are ordered, and the electrode kinetics are lumped into a single charge transfer resistance parameter. We then demonstrate the practical estimation of model parameters from measured frequency-domain experimental electrochemical impedance spectroscopy (EIS) data, and show additionally that the parametrised model provides good predictive capabilities in the time domain, exhibiting a maximum voltage error of 20 mV between model and experiment over a 10 minute dynamic discharge.Comment: 16 pages, 9 figures, pre-print submitted to the IEEE Transactions on Control Systems Technolog

A hardware-in-the-loop test rig for development of electric vehicle battery identification and state estimation algorithms

This paper describes a hardware-in-the-loop (HIL) test rig for the test and development of electric vehicle battery parameterisation and state-estimation algorithms in the presence of realistic real-world duty cycles. The rig includes two electric machines, a battery pack, a real-time simulator, a thermal chamber and a PC for human-machine interface. Other parts of a vehicle powertrain system are modelled and used in the real-time simulator. A generic framework has been developed for real-time battery measurement, model identification and state estimation. Measurements are used to extract parameters of an equivalent circuit network model. Outputs of the identification unit are then used by an estimation unit trained to find the relationship between the battery parameters and state-of-charge. The results demonstrate that even with a high noise level in measured data, the proposed identification and estimation algorithms are able to work well in real-time

A review of fractional-order techniques applied to lithium-ion batteries, lead-acid batteries, and supercapacitors

Electrochemical energy storage systems play an important role in diverse applications, such as electrified transportation and integration of renewable energy with the electrical grid. To facilitate model-based management for extracting full system potentials, proper mathematical models are imperative. Due to extra degrees of freedom brought by differentiation derivatives, fractional-order models may be able to better describe the dynamic behaviors of electrochemical systems. This paper provides a critical overview of fractional-order techniques for managing lithium-ion batteries, lead-acid batteries, and supercapacitors. Starting with the basic concepts and technical tools from fractional-order calculus, the modeling principles for these energy systems are presented by identifying disperse dynamic processes and using electrochemical impedance spectroscopy. Available battery/supercapacitor models are comprehensively reviewed, and the advantages of fractional types are discussed. Two case studies demonstrate the accuracy and computational efficiency of fractional-order models. These models offer 15–30% higher accuracy than their integer-order analogues, but have reasonable complexity. Consequently, fractional-order models can be good candidates for the development of advanced b attery/supercapacitor management systems. Finally, the main technical challenges facing electrochemical energy storage system modeling, state estimation, and control in the fractional-order domain, as well as future research directions, are highlighted

Assessment of element-specific recycling efficiency in WEEE pre-processing

Pre-processing is a crucial step to ensure the efficiency of subsequent processes and the quality of recyclates. The efficiency of pre-processing can be affected by high losses to undesignated output fractions. Standard batch tests usually provide mass balances and are a good proxy for bulk materials balances (iron/steel, aluminum, plastics). This article aims at harmonizing methodologies and recommends a strategy for further study in pre-processing on a plant scale. We have developed an “extended batch test” method, which should help to • describe the fates of materials and elements, • assess the quality of output fractions, • identify access points for critical metals and other valuable elements to enable their recovery. A methodical approach was compiled with common material flow analysis methods and an extended set of methods, which improve the reliability via the assessment of uncertainties. This applies to systematic effects and random effects. This extended batch test was performed with a 40 Mg Waste Electrical & Electronic Equipment (WEEE) batch to trace the flows of industrial base metals, precious metals and critical metals in a WEEE pre-processing plant. Results show that one-third of the input was separated and sorted manually, while the remaining material was subsequently crushed and automatically sorted. Copper and precious metals are distributed to various output fractions but are most concentrated in the sorting residues. Critical metals like cobalt and rare earth elements are mainly concentrated in the manually sorted materials but also appear in the ferrous metals scrap and the shredder light fraction

Phase 1 of the near term hybrid passenger vehicle development program. Appendix B: Trade-off studies, volume 1

Tradeoff study activities and the analysis process used are described with emphasis on (1) review of the alternatives; (2) vehicle architecture; and (3) evaluation of the propulsion system alternatives; interim results are presented for the basic hybrid vehicle characterization; vehicle scheme development; propulsion system power and transmission ratios; vehicle weight; energy consumption and emissions; performance; production costs; reliability, availability and maintainability; life cycle costs, and operational quality. The final vehicle conceptual design is examined

Automated tracking of the Florida manatee (Trichechus manatus)

The electronic, physical, biological and environmental factors involved in the automated remote tracking of the Florida manatee (Trichechus manatus) are identified. The current status of the manatee as an endangered species is provided. Brief descriptions of existing tracking and position locating systems are presented to identify the state of the art in these fields. An analysis of energy media is conducted to identify those with the highest probability of success for this application. Logistic questions such as the means of attachment and position of any equipment to be placed on the manatee are also investigated. Power sources and manateeborne electronics encapsulation techniques are studied and the results of a compter generated DF network analysis are summarized

Electric vehicle battery management algorithm development using a HIL simulator incorporating three-phase machines and power electronics

This paper describes a hardware-in-the-loop (HIL) test rig for the test and development of electric vehicle battery management and state-estimation algorithms in the presence of realistic real-world duty cycles. The rig includes two back-to-back connected brushless DC motors, the respective power electronic controllers, a target battery pack, a dSPACE real-time simulator, a thermal chamber and a PC for human-machine interface. The traction motor is commanded to track a reference velocity based on a drive cycle and the target battery pack provides the required power. Except the battery pack and the electric machine which are real, other parts of a vehicle powertrain system are modelled and used in the real-time simulator. A generic framework has been developed for real-time battery measurement, model identification and state estimation. Measurements of current and battery terminal voltage are used by an identification unit to extract parameters of an equivalent circuit network (ECN) model in real-time. Outputs of the identification unit are then used by an estimation unit which uses an artificial intelligent model trained to find the relationship between the battery parameters and state-of-charge (SOC). The results demonstrate that even with a high noise level in measured data, the proposed identification and estimation algorithms are able to work well in real-time

Model-based prognostics for batteries which estimates useful life and uses a probability density function

This invention develops a mathematical model to describe battery behavior during individual discharge cycles as well as over its cycle life. The basis for the form of the model has been linked to the internal processes of the battery and validated using experimental data. Effects of temperature and load current have also been incorporated into the model. Subsequently, the model has been used in a Particle Filtering framework to make predictions of remaining useful life for individual discharge cycles as well as for cycle life. The prediction performance was found to be satisfactory as measured by performance metrics customized for prognostics for a sample case. The work presented here provides initial steps towards a comprehensive health management solution for energy storage devices

Estimation Strategies for the Condition Monitoring of a Battery Systemin a Hybrid Electric Vehicle

This paper discusses the application of condition monitoring to a battery system used in a hybrid electric vehicle (HEV). Battery condition management systems (BCMSs) are employed to ensure the safe, efficient, and reliable operation of a battery, ultimately to guarantee the availability of electric power. This is critical for the case of the HEV to ensure greater overall energy efficiency and the availability of reliable electrical supply. This paper considers the use of state and parameter estimation techniques for the condition monitoring of batteries. A comparative study is presented in which the Kalman and the extended Kalman filters (KF/EKF), the particle filter (PF), the quadrature Kalman filter (QKF), and the smooth variable structure filter (SVSF) are used for battery condition monitoring. These comparisons are made based on estimation error, robustness, sensitivity to noise, and computational time.Comment: 18 pages, 16 figures, ISRN Signal Processing, 201

Prognostics and health management for maintenance practitioners - Review, implementation and tools evaluation.

In literature, prognostics and health management (PHM) systems have been studied by many researchers from many different engineering fields to increase system reliability, availability, safety and to reduce the maintenance cost of engineering assets. Many works conducted in PHM research concentrate on designing robust and accurate models to assess the health state of components for particular applications to support decision making. Models which involve mathematical interpretations, assumptions and approximations make PHM hard to understand and implement in real world applications, especially by maintenance practitioners in industry. Prior knowledge to implement PHM in complex systems is crucial to building highly reliable systems. To fill this gap and motivate industry practitioners, this paper attempts to provide a comprehensive review on PHM domain and discusses important issues on uncertainty quantification, implementation aspects next to prognostics feature and tool evaluation. In this paper, PHM implementation steps consists of; (1) critical component analysis, (2) appropriate sensor selection for condition monitoring (CM), (3) prognostics feature evaluation under data analysis and (4) prognostics methodology and tool evaluation matrices derived from PHM literature. Besides PHM implementation aspects, this paper also reviews previous and on-going research in high-speed train bogies to highlight problems faced in train industry and emphasize the significance of PHM for further investigations