The battery management system (BMS) is an integral part of automobile. It protects the from damage, predicts life, and maintains in operational condition. BMS performs these tasks by integrating one or more functions, such as protecting cell, thermal management, controlling charge-discharge, determining state charge (SOC), health (SOH), remaining useful life (RUL) battery, cell balancing, data acquisition, communication with on-board off-board modules, well monitoring storing historical...

Battery management system (BMS) is an integral part of automobile. It protects the battery from damage, predicts life and maintains in operational condition. The BMS performs these tasks by integrating one or more functions, such as protecting cell, controlling charge, determining state charge (SOC), health (SOH), remaining useful (RUL) battery, cell balancing, well monitoring storing historical data. In this paper, we propose a that estimates three critical characteristics (SOC, SOH, RUL)...

Recent advances in sensor technology, remote communication and computational capabilities, standardized hardware/software interfaces are creating a dramatic shift the way health of vehicles is monitored managed. Concomitantly, there an increased trend towards forecasting system degradation through prognostic process to fulfill needs customers demanding high vehicle availability. Prognosis viewed as add-on capability diagnosis that assesses current predicts its remaining life based on sensed...

Regenerative braking is one of the most promising and environmentally friendly technologies used in electric hybrid vehicles to improve energy efficiency vehicle stability. This paper presents a systematic data-driven process for detecting diagnosing faults regenerative system vehicles. The diagnostic involves signal processing statistical techniques feature extraction, data reduction implementation memory-constrained electronic control units, variety fault classification methodologies...

Regenerative braking is one of the most promising and environmentally friendly technologies used in electric hybrid vehicles to improve energy efficiency vehicle stability. In this paper, we discuss a systematic data-driven process for detecting diagnosing faults regenerative system vehicles. The involves data reduction techniques, exemplified by multi-way partial least squares, principal component analysis, implementation memory-constrained electronic control units well-known fault...

In this paper, we discuss the battery health degradation and optimal life management. As first contribution of how manifests itself as capacity fading due to repeated charging discharging cycles. We present two models, namely, LAR-αβγ CVD (control variable-dependent) regression for fade modeling, which are characterized functions number cycles charge control parameters, viz., maximum terminal voltage current. The development these models is based on curve-fitting data from copious aging...

In this paper, we present a novel SOC tracking algorithm for Li-ion batteries. The proposed approach employs voltage drop model that avoid the need modeling hysteresis effect in battery. Our results reduced order (single state) filtering where no additional variables to be tracked regardless of level complexity battery equivalent model. We identify presence correlated noise has been so far ignored literature and use improved tracking. performs within 1% or better accuracy based on both...

The open circuit voltage (OCV) characterization of Li-ion batteries as it applies to battery fuel gauging (BFG) in portable applications is considered this paper. Accurate knowledge the nonlinear relationship between OCV and state charge (SOC) required for adaptive SOC tracking during usage. BFG requires OCV-SOC be defined with a minimum number parameters. With help data collected from 34 cells each at 16 different temperatures ranging -25°C 50°C, we present novel normalized modeling...

The key objectives of this paper are to analyze and implement a novel moving horizon model predictive estimation scheme based on constrained nonlinear optimization techniques for inferring the survival functions residual useful life (RUL) components in coupled systems. approach employs data-driven prognostics framework that combines failure time data, static dynamic (time-series) parametric Multiple Model Moving Horizon Estimation (MM-MHE) algorithm predicting their usage profiles....

In this paper we present an approach for robust, real time capacity estimation in Li-ion batteries. The proposed scheme has the following novel features: it employes total least squares (TLS) order to account uncertainties both model and observations estimation. TLS method can adaptively track changes battery capacity. We propose a second estimate by exploiting rest states battery. This is devised minimize effect of hysteresis Finally, optimally fusing estimates obtained through different...

In this paper, we present a novel voltage drop model for battery SOC tracking and develop robust, realtime approach parameter estimation. The proposed avoids the need to hysteresis that hard estimate in practical applications. Another advantage of is parameters estimated linearly, regardless complexity, i.e., number RC elements considered model. We identify presence correlated noise has been so far ignored literature use it enhance accuracy identification. enables robust...

Contemporary Battery Management Systems (BMS) form an essential part of a wide range devices, such as portable electronics, mobiles, personal digital assistants (PDAs), hybrid and electric vehicles, aerospace equipment. In this paper, we propose novel closed-loop integrated BMS consisting battery fuel gauge (BFG) optimal charging algorithms (OCAs). The system not only performs accurate estimation the state batteries, charge (SOC), slate health (SOH) remaining useful lire (RliL), but also...


 The Electronic Return-less Fuel System (ERFS) manages the delivery of fuel from tank to engine. pressure in line is electronically controlled by system control module speeding up or slowing down pump. This allows efficiently amount provided engine when compared vehicles equipped with a standard wherein pump continuously runs at full speed. A failure that impacts ability deliver will have an immediate effect on performance. Consequently, improved reliability and availability, reduction...

This article presents a novel MM-MHE algorithm for online prediction of the component survival functions based on their usage profiles. The framework employs Cox PHM offline and data RUL prediction. proposed approach has been validated by way application to derived from an automotive ETC system simulator. shows excellent performance (R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> MSE) in presence significant measurement noise over all...