Caihao Weng

An Open-Circuit-Voltage Model of Lithium-Ion Batteries for Effective Incremental Capacity Analysis

Open-Circuit-Voltage (OCV) is an essential part of battery models for state-of-charge (SOC) estimation. In this paper, we propose a new parametric OCV model, which considers the staging phenomenon during the lithium intercalation/deintercalation process. Results show that the new parametric model improves SOC estimation accuracy compared to other existing OCV models. Moreover, the model is shown to be suitable and effective for battery state-of-health monitoring. In particular, the new OCV model can be used for incremental capacity analysis (ICA), which reveals important information on the cell behavior associated with its electrochemical properties and aging status.

Model Parametrization and Adaptation Based on the Invariance of Support Vectors With Applications to Battery State-of-Health Monitoring

Support vector regression (SVR) algorithms have been applied to the identification of many nonlinear dynamic systems due to their excellent approximation and generalization capability. However, the standard SVR algorithm involves an iterative optimization process, which is often computationally expensive and inefficient. For applications such as the battery state-of-health (SOH) monitoring, where the identification algorithm needs to be applied repeatedly for multiple cells because of the variation in model dynamics (due to battery aging and cell-to-cell difference), the computational burden could pose difficulties for real-time or onboard implementation. In this paper, the battery V -Q curve identification problem for SOH monitoring is studied. Based on experimental battery aging data, we develop a model parametrization and adaptation framework utilizing the simple structure of SVR representation with determined support vectors (SVs) so that the model parameters can be estimated in real time. Through mathematical analysis and simulations using a mechanistic battery aging model, it is shown that the SVs of the battery models stay invariant, even when the batteries age or vary. The invariance of the SVs is verified using experimental aging data. Consequently, the resulting model for the battery V -Q curve can be directly incorporated into the battery management system (BMS) and adapted online for SOH monitoring. Moreover, the general characteristics of the data that could maintain the SVR invariance are identified. The proposed automated model parametrization process (via an optimization algorithm) can be extended to nonlinear dynamic systems with the given properties.

Optimal control of hybrid electric vehicles with power split and torque split strategies: A comparative case study

In designing control strategies to optimize fuel consumption, driveability and other objectives for hybrid electric vehicles (HEVs), one can choose to use either power split or torque split as one of the control variables. While both approaches have been employed and documented, no systematic study has been reported that illuminates what implications this choice might have in terms of HEV performance, system robustness, and control strategy design and implementation complexity. This work aims to develop a case study that explores this degree of design freedom and to quantify any differences that this control design selection might impart on a given HEV architecture. Using a validated HEV model, we will derive optimal operating strategies using dynamic programming for two cases: one uses power split and other torque split. Performance metrics of fuel consumption as well as the computational complexity associated with the two different strategies will be assessed.

Design of a Variable Geometry Turbine control strategy for Solid Oxide Fuel Cell and Gas Turbine hybrid systems

Solid Oxide Fuel Cell (SOFC) and Gas Turbine (GT) hybrid systems have been widely studied in recent years as a promising alternative power sources for various applications. The fundamental concept of this system is combining a GT with the SOFC system to recuperate the energy left in the SOFC exhaust, thereby improving the overall system efficiency. However, because of the coupling dynamics between SOFC and GT, the system is susceptible to shutdown in the case of an abrupt load change. This work investigates the use of the Variable Geometry Turbine (VGT) to address this shutdown problem and improve the transient system performance. A model of a 60-kW class SOFC/GT hybrid system is developed for the study. Based on the insights learned from the open-loop analysis, a feedback design is proposed for VGT control, analysis of transient dynamics for the closed-loop is performed, and simulation results demonstrating the performance are presented.