scholarly journals A Review of Battery State of Health Estimation Methods: Hybrid Electric Vehicle Challenges

2020 ◽  
Vol 11 (4) ◽  
pp. 66
Author(s):  
Nassim Noura ◽  
Loïc Boulon ◽  
Samir Jemeï
Keyword(s):  
Real Time ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicle ◽  
High Performance ◽  
Health Management ◽  
Estimation Method ◽  
Time Estimation ◽  
Estimation Methods ◽  
State Of Health ◽  
Hybrid Electric

To cope with the new transportation challenges and to ensure the safety and durability of electric vehicles and hybrid electric vehicles, high performance and reliable battery health management systems are required. The Battery State of Health (SOH) provides critical information about its performances, its lifetime and allows a better energy management in hybrid systems. Several research studies have provided different methods that estimate the battery SOH. Yet, not all these methods meet the requirement of automotive real-time applications. The real time estimation of battery SOH is important regarding battery fault diagnosis. Moreover, being able to estimate the SOH in real time ensure an accurate State of Charge and State of Power estimation for the battery, which are critical states in hybrid applications. This study provides a review of the main battery SOH estimation methods, enlightening their main advantages and pointing out their limitations in terms of real time automotive compatibility and especially hybrid electric applications. Experimental validation of an online and on-board suited SOH estimation method using model-based adaptive filtering is conducted to demonstrate its real-time feasibility and accuracy.

Multirate Integration in Hybrid Electric Vehicle Virtual Proving Grounds

1998 ◽  
Author(s):  
Dario Solis ◽  
Chris Schwarz
Keyword(s):  
Real Time ◽  
Electric Vehicle ◽  
Time Scales ◽  
Electric Vehicles ◽  
Time Scale ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric Vehicles ◽  
Differential Algebraic Equations ◽  
Vehicle Systems ◽  
Hybrid Electric

Abstract In recent years technology development for the design of electric and hybrid-electric vehicle systems has reached a peak, due to ever increasing restrictions on fuel economy and reduced vehicle emissions. An international race among car manufacturers to bring production hybrid-electric vehicles to market has generated a great deal of interest in the scientific community. The design of these systems requires development of new simulation and optimization tools. In this paper, a description of a real-time numerical environment for Virtual Proving Grounds studies for hybrid-electric vehicles is presented. Within this environment, vehicle models are developed using a recursive multibody dynamics formulation that results in a set of Differential-Algebraic Equations (DAE), and vehicle subsystem models are created using Ordinary Differential Equations (ODE). Based on engineering knowledge of vehicle systems, two time scales are identified. The first time scale, referred to as slow time scale, contains generalized coordinates describing the mechanical vehicle system that includs the chassis, steering rack, and suspension assemblies. The second time scale, referred to as fast time scale, contains the hybrid-electric powertrain components and vehicle tires. Multirate techniques to integrate the combined set of DAE and ODE in two time scales are used to obtain computational gains that will allow solution of the system’s governing equations for state derivatives, and efficient numerical integration in real time.

Multi-Layer Mini-Channel and Ribbed Mini-Channel Based High Performance Cooling Configurations for Automotive Inverters—Part A: Design and Evaluation

2013 ◽  
Vol 5 (3) ◽  
Author(s):  
Pritish R. Parida ◽  
Srinath V. Ekkad ◽  
Khai Ngo
Keyword(s):  
Power Control ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicle ◽  
High Performance ◽  
Heat Dissipation ◽  
Cooling System ◽  
Control Unit ◽  
Consumer Products ◽  
Hybrid Electric

Necessitated by the dwindling supply of petroleum resources, various new automotive technologies have been actively developed from the perspective of achieving energy security and diversifying energy sources. Hybrid electric vehicles and electric vehicles are a few such examples. Such diversification requires the use of power control units essentially for power control, power conversion, and power conditioning applications such as variable speed motor drives (dc–ac conversion), dc–dc converters and other similar devices. The power control unit of a hybrid electric vehicle or electric vehicle is essentially the brain of the hybrid system as it manages the power flow between the electric motor generator, battery and gas engine. Over the last few years, the performance of this power control unit has been improved and size has been reduced to attain higher efficiency and performance, causing the heat dissipation as well as heat density to increase significantly. Efforts are constantly being made to reduce this size even further. As a consequence, a better high performance cooler/heat exchanger is required to maintain the active devices temperature within optimum range. Cooling schemes based on multiple parallel channels are a few solutions which have been widely used to dissipate transient and steady concentrated heat loads and can be applied to existing cooling system with minor modifications. The aim of the present study has therefore been to study the various cooling options based on mini-channel and rib-turbulated mini-channel cooling for application in a hybrid electric vehicle and other similar consumer products, and perform a parametric and optimization study on the selected designs. Significant improvements in terms of thermal performance, reduced overall pressure drop, and volume reduction have been shown both experimentally and numerically. This paper is the first part in a two part submission and focuses on the design and evaluation of mini-channel and rib-turbulated mini-channel cooling configurations. The second part of this paper discusses the manufacturing and testing of the cooling device.

Parametric Vehicular Simulator in the Evaluation of HELVIS Mini-HEV EDS Control

2011 ◽  
Author(s):  
Rafael C. B. Sampaio ◽  
Gabriel S. de Lima ◽  
Vinicius V. M. Fernandes ◽  
Andre´ C. Hernandes ◽  
Marcelo Becker
Keyword(s):  
Artificial Intelligence ◽  
Experimental Data ◽  
Real Time ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Differential System ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric Vehicles ◽  
Hybrid Electric ◽  
The Universe

HELVIS (Hybrid Electric Vehicle In Low Scale) is a mini-HEV platform used on the research of HEVs (Hybrid Electric Vehicles), through which students of all degrees have the opportunity to be introduced to the universe that surrounds HEVs in many aspects. In this work the HELVIS-Sim is presented. HELVIS-Sim is a full dynamic & kinematic vehicular simulator for the HELVIS platform, consisting of a Simulink™ environment through which the states of a large number of variables related to the vehicle can be observed and analyzed. Specially in this paper, the focus is in the control of HELVIS EDS (Electronic Differential System), presenting classic, A.I.-based (Artificial Intelligence) and optimal robust controllers in the problem of the adjustment of the rear angular speeds. HELVIS-Sim results are then compared to experimental data obtained from the real HELVIS EDS, with the aid of a dSpace™ real time interface board.

Study of Vehicle Sideslip Angle Real-Time Estimation Method

2013 ◽  
Vol 846-847 ◽  
pp. 26-29
Author(s):  
Xiao Bin Fan ◽  
Pan Deng
Keyword(s):  
Real Time ◽  
Estimation Method ◽  
Time Estimation ◽  
Stability Control ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Slip Angle ◽  
Sideslip Angle ◽  
Direct Integration Method ◽  
Real Time Estimation

In the vehicle stability control and other active safety systems, vehicle sideslip angle real-time estimation is necessary. However, the direct measurement of sideslip angle is more difficult or too costly, so it is often used in estimating methods. The vehicle sideslip angle of closed-loop Luenberger observer and Kalman observer were constructed based on two degrees of freedom bicycle model, as well as the direct integration method for large sideslip angle conditions. The comparative study showed that Kalman filtering estimation method and Luenberger estimation methods have better estimation accuracy in small slip angle range.

scholarly journals A Review of State of Health Estimation of Energy Storage Systems: Challenges and Possible Solutions for Futuristic Applications of Li-Ion Battery Packs in Electric Vehicles

2019 ◽  
Vol 16 (4) ◽  
Author(s):  
Sudipta Bijoy Sarmah ◽  
Pankaj Kalita ◽  
Akhil Garg ◽  
Xiao-dong Niu ◽  
Xing-Wei Zhang ◽  
...  
Keyword(s):  
Real Time ◽  
Electric Vehicles ◽  
Lithium Ion ◽  
Time Estimation ◽  
State Of Health ◽  
Li Ion Battery ◽  
Super Capacitor ◽  
Advantages And Disadvantages ◽  
Battery Packs ◽  
Li Ion

Lithium-ion (Li-ion) battery pack is vital for storage of energy produced from different sources and has been extensively used for various applications such as electric vehicles (EVs), watches, cookers, etc. For an efficient real-time monitoring and fault diagnosis of battery operated systems, it is important to have a quantified information on the state-of-health (SoH) of batteries. This paper conducts comprehensive literature studies on advancement, challenges, concerns, and futuristic aspects of models and methods for SoH estimation of batteries. Based on the studies, the methods and models for SoH estimation have been summarized systematically with their advantages and disadvantages in tabular format. The prime emphasis of this review was attributed toward the development of a hybridized method which computes SoH of batteries accurately in real-time and takes self-discharge into its account. At the end, the summary of research findings and the future directions of research such as nondestructive tests (NDT) for real-time estimation of battery SoH, finding residual SoH for the recycled batteries from battery packs, integration of mechanical aspects of battery with temperature, easy assembling–dissembling of battery packs, and hybridization of battery packs with photovoltaic and super capacitor are discussed.

scholarly journals Real-Time Estimation of Drivers’ Trust in Automated Driving Systems

2020 ◽  
Author(s):  
Hebert Azevedo-Sa ◽  
Suresh Kumaar Jayaraman ◽  
Connor T. Esterwood ◽  
X. Jessie Yang ◽  
Lionel P. Robert ◽  
...  
Keyword(s):  
Real Time ◽  
User Study ◽  
Estimation Method ◽  
Time Estimation ◽  
Trust Model ◽  
Estimation Methods ◽  
Model Parameters ◽  
Automated Driving ◽  
Driving System ◽  
Classical State

Abstract Trust miscalibration issues, represented by undertrust and overtrust, hinder the interaction between drivers and self-driving vehicles. A modern challenge for automotive engineers is to avoid these trust miscalibration issues through the development of techniques for measuring drivers’ trust in the automated driving system during real-time applications execution. One possible approach for measuring trust is through modeling its dynamics and subsequently applying classical state estimation methods. This paper proposes a framework for modeling the dynamics of drivers’ trust in automated driving systems and also for estimating these varying trust levels. The estimation method integrates sensed behaviors (from the driver) through a Kalman filter-based approach. The sensed behaviors include eye-tracking signals, the usage time of the system, and drivers’ performance on a non-driving-related task. We conducted a study ($$n=80$$ n = 80 ) with a simulated SAE level 3 automated driving system, and analyzed the factors that impacted drivers’ trust in the system. Data from the user study were also used for the identification of the trust model parameters. Results show that the proposed approach was successful in computing trust estimates over successive interactions between the driver and the automated driving system. These results encourage the use of strategies for modeling and estimating trust in automated driving systems. Such trust measurement technique paves a path for the design of trust-aware automated driving systems capable of changing their behaviors to control drivers’ trust levels to mitigate both undertrust and overtrust.

scholarly journals Real-Time Energy Management of Parallel Hybrid Electric Vehicles Using Linear Quadratic Regulation

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5538
Author(s):  
Bảo-Huy Nguyễn ◽  
João Pedro F. Trovão ◽  
Ronan German ◽  
Alain Bouscayrol
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Engine Fuel ◽  
Linear Quadratic ◽  
Loop Control ◽  
Parallel Hybrid ◽  
Linear Quadratic Regulation ◽  
Hybrid Electric

Optimization-based methods are of interest for developing energy management strategies due to their high performance for hybrid electric vehicles. However, these methods are often complicated and may require strong computational efforts, which can prevent them from real-world applications. This paper proposes a novel real-time optimization-based torque distribution strategy for a parallel hybrid truck. The strategy aims to minimize the engine fuel consumption while ensuring battery charge-sustaining by using linear quadratic regulation in a closed-loop control scheme. Furthermore, by reformulating the problem, the obtained strategy does not require the information of the engine efficiency map like the previous works in literature. The obtained strategy is simple, straightforward, and therefore easy to be implemented in real-time platforms. The proposed method is evaluated via simulation by comparison to dynamic programming as a benchmark. Furthermore, the real-time ability of the proposed strategy is experimentally validated by using power hardware-in-the-loop simulation.

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