Battery health monitoring and management is of extreme importance for the performance cost electric vehicles. This paper concerned with machine-learning-enabled battery state-of-health (SOH) indication prognosis. The sample entropy short voltage sequence used as an effective signature capacity loss. Advanced sparse Bayesian predictive modeling (SBPM) methodology employed to capture underlying correspondence between loss entropy. SBPM-based SOH monitor compared a polynomial model developed in...

The potential for reduced fuel consumption of hybrid electric vehicles by the use predictive powertrain control was assessed on measured-drive data from an urban route with varying topography. assessment done evaluating using three optimal controllers, each a different level information access to driven route. lowest case represents that vehicle knows it is being in certain environment, e.g., city driving, and controller has been optimized type environment. second highest equipped GPS...

This paper is concerned with the simultaneous optimal component sizing and power management of a fuel cell/battery hybrid bus. Existing studies solve combined plant/controller optimization problem for cell vehicles (FCHVs) by using methods disadvantages heavy computational burden and/or suboptimality, which only single driving profile was often considered. adds three important contributions to FCHVs-related literature. First, convex programming extended rapidly efficiently optimize both...

This paper comparatively examines three different electrochemical energy storage systems (ESSs), i.e., a Li-ion battery pack, supercapacitor and dual buffer, for hybrid bus powertrain operated in Gothenburg, Sweden. Existing studies focus on comparing these ESSs, terms of either general attributes (e.g., density power density) or their implications to the fuel economy vehicles with heuristic/nonoptimal ESS size management strategy. adds four original contributions related literature. First,...

This brief presents an integrated optimization framework for battery sizing, charging, and on-road power management in plug-in hybrid electric vehicles. utilizes convex programming to assess interactions between the three optimal design/control tasks. The objective is minimize carbon dioxide (CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) emissions, from on-board internal combustion engine grid generation plants providing...

Fast charging strategies have gained an increasing interest toward the convenience of battery applications but may unduly degrade or damage batteries. To harness these competing objectives, including safety, lifetime, and time, this paper proposes a health-aware fast strategy synthesized from electrochemical system modeling advanced control theory. The problem is formulated in linear time-varying model predictive algorithm. In algorithm, control-oriented electrochemical-thermal developed to...

Efficient battery condition monitoring is of particular importance in large-scale, high-performance, and safety-critical mechatronic systems, e.g., electrified vehicles smart grid. This paper pursues a detailed assessment optimization-driven moving horizon estimation (MHE) framework by means reduced electrochemical model. For state-of-charge estimation, the standard MHE two variants are examined comprehensive consideration accuracy, computational intensity, effect size, fault tolerance. A...

System integration and power-flow control of on-board power sources are critical to the performance cost competitiveness hybrid electric vehicles (HEVs). The existing methods mostly focus on fuel minimization in powertrains, while disregarding many other concerns. This article presents an innovative multicriteria optimization approach showcases its validity usefulness a case study fuel-cell bus. Three key technical contributions made. First, convex framework is devised for quickly...

This paper introduces a novel method for the simultaneous optimization of energy management and powertrain component sizing parallel plug-in hybrid electric vehicle (PHEV). The problem is formulated as convex to minimize an objective function, which weighted sum operational costs. cost includes consumed fossil fuel electrical energy, whereas battery, motor (EM), internal combustion engine (ICE). model quadratic losses components. Moreover, are assumed linearly scale with respect size...

This paper is concerned with model-based dynamic peak-power evaluation for LiNMC and LiFePO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sub> batteries under different operating conditions. The battery test our prior study on linear-parameter-varying (LPV) modeling are briefly introduced. estimation method that incorporates an explicit prediction horizon design constraints the current, voltage, SOC elaborated, its computational load...

The computationally demanding dynamic programming (DP) algorithm is frequently used in academic research to solve the energy management problem of a hybrid electric vehicle (HEV). This paper exclusively focused on how computational demand such computation can be reduced. main idea use local approximation gridded cost-to-go and derive an analytic solution for optimal torque split decision at each point time state grid. Thereby, it not necessary quantize identify by interpolating cost-to-go....

The electrification of road transport is accelerating globally, propelled by a mix environmental concerns, legislative mandates, and business opportunities. Relying to larger extent on electricity in the transportation sector provides new opportunities reduce carbon dioxide (CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) emissions, fossil fuel consumption, local air pollution improving energy efficiency employing renewable energy....

Thermal and state-of-charge (SOC) imbalances are well known to cause nonuniform aging in batteries. This paper presents the electrothermal control of a multilevel converter-based modular battery address this issue. The provides large redundancy synthesizing terminal voltage, which gives extra degrees freedom on cell level. There multiple tightly coupled objectives including simultaneous thermal SOC balancing as voltage control. main purpose is devise an scheme for cases where full future...

Modeling and control of hybrid systems, with particular emphasis on process applications, are considered in this article. Based a number observations typical mixed discrete continuous features for such fairly general model structure systems is proposed. This structure, which clearly separates the open-loop plant from closed-loop system, suitable analysis synthesis systems. To illustrate this, three different approaches control-law based specifications discussed. In first one, replaced by...

Pisarenko's harmonic retrieval method involves determining the minimum eigenvalue and corresponding eigenvector of covariance matrix observed random process. Recently, Thompson [9] suggested a constrained gradient search procedure for obtaining an adaptive version method, his simulations have verified that frequency estimates provided by were unbiased. However, main cost this technique was initial convergence rate could be very slow certain poor conditions. Restating minimization as...

In automotive powertrains, backlash imposes well-known limitations on the quality of control and, hence, vehicle driveability. High-performance controllers for compensation require high-quality measurements current state powertrain. Information about size is also needed. this paper, nonlinear estimators and are developed, using Kalman filtering theory. A linear estimator fast accurate estimation angular position a wheel engine described. It utilizes standard speed sensors antilock brake...