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Journal Article

A Combination of Intelligent Tire and Vehicle Dynamic Based Algorithm to Estimate the Tire-Road Friction

2019-04-08
Abstract One of the most important factors affecting the performance of vehicle active chassis control systems is the tire-road friction coefficient. Accurate estimation of the friction coefficient can lead to better performance of these controllers. In this study, a new three-step friction estimation algorithm, based on intelligent tire concept, is proposed, which is a combination of experiment-based and vehicle dynamic based approaches. In the first step of the proposed algorithm, the normal load is estimated using a trained Artificial Neural Network (ANN). The network was trained using the experimental data collected using a portable tire testing trailer. In the second step of the algorithm, the tire forces and the wheel longitudinal velocity are estimated through a two-step Kalman filter. Then, in the last step, using the estimated tire normal load and longitudinal and lateral forces, the friction coefficient can be estimated.
Journal Article

Parasitic Battery Drain Problems and AUTOSAR Acceptance Testing

2018-04-18
Abstract Battery Drain problems can occur in the vehicle due to improper network management between electronic control units (ECUs). Aim of this paper is to identify the factors that cause transmission and cease of transmission of a network management message of an ECU along with its application messages that controls the sleep/wake-up performance of other ECUs in the network. Strategy used here is, based on the root cause analysis of problems found in Display unit in vehicle environment, the functional CAN signals impacting sleep/wake-up behavior is re-mapped along with the state flow transition of AUTOSAR NM Algorithm. A re-defined test case design and simulation for vehicle model is created. Especially it focuses on validating the impact of functional CAN signals on DUT’s sleep/wake-up performance.
Journal Article

An Adaptive Neuro-Fuzzy Inference System (ANFIS) Based Model for the Temperature Prediction of Lithium-Ion Power Batteries

2018-08-14
Abstract Li-ion batteries have been widely applied in the areas of personal electronic devices, stationary energy storage system and electric vehicles due to their high energy/power density, low self-discharge rate and long cycle life etc. For the better designs of both the battery cells and their thermal management systems, various numerical approaches have been proposed to investigate the thermal performance of power batteries. Without the requirement of detailed physical and thermal parameters of batteries, this article proposed a data-driven model using the adaptive neuro-fuzzy inference system (ANFIS) to predict the battery temperature with the inputs of ambient temperature, current and state of charge. Thermal response of a Li-ion battery module was experimentally evaluated under various conditions (i.e. ambient temperature of 0, 5, 10, 15 and 20 °C, and current rate of C/2, 1C and 2C) to acquire the necessary data sets for model development and validation.
Journal Article

Experimental Study on the Internal Resistance and Heat Generation Characteristics of Lithium Ion Power Battery with NCM/C Material System

2018-04-18
Abstract Heat generation characteristics of lithium ion batteries are vital for both the optimization of the battery cells and thermal management system design of battery packs. Compared with other factors, internal resistance has great influence on the thermal behavior of Li-ion batteries. Focus on a 3 Ah pouch type battery cell with the NCM/C material system, this paper quantitatively evaluates the battery heat generation behavior using an Extended Volume-Accelerating Rate Calorimeter in combination with a battery cycler. Also, internal resistances of the battery cell are measured using both the hybrid pulse power characteristic (HPPC) and electro-chemical impedance spectroscopy (EIS) methods. Experimental results show that the overall internal resistance obtained by the EIS method is close to the ohmic resistance measured by the HPPC method. Heat generation power of the battery cell is small during discharge processes lower than 0.5 C-rate.
Journal Article

Personalized Controller Design for Electric Power Steering System Based on Driver Behavior

2017-09-23
Abstract Electric power steering (EPS) system is a kind of dynamic control system for vehicle steering, which can amplify the driver steering torque inputs to the vehicle to improve steering comfortable and performance, but the present EPS can’t cater to the driving habits of different people. In this paper, a personalized EPS controller is designed based on the driver behavior, which combines real-time driver behavior identification strategy with personalized assistance characteristic. Firstly, the driver behavior data acquisition system is designed and established, based on which, the input data of different kinds of drivers along with vehicle signals are collected under typical working conditions, then the identification of driver behavior online is realized using the BP neural network.
Journal Article

3D Scene Reconstruction with Sparse LiDAR Data and Monocular Image in Single Frame

2017-09-23
Abstract Real-time reconstruction of 3D environment attributed with semantic information is significant for a variety of applications, such as obstacle detection, traffic scene comprehension and autonomous navigation. The current approaches to achieve it are mainly using stereo vision, Structure from Motion (SfM) or mobile LiDAR sensors. Each of these approaches has its own limitation, stereo vision has high computational cost, SfM needs accurate calibration between a sequences of images, and the onboard LiDAR sensor can only provide sparse points without color information. This paper describes a novel method for traffic scene semantic segmentation by combining sparse LiDAR point cloud (e.g. from Velodyne scans), with monocular color image. The key novelty of the method is the semantic coupling of stereoscopic point cloud with color lattice from camera image labelled through a Convolutional Neural Network (CNN).
Journal Article

Hydro-Pneumatic Energy Harvesting Suspension System Using a PSO Based PID Controller

2018-08-01
Abstract In this article, a unique design for Hydro-Pneumatic Energy Harvesting Suspension HPEHS system is introduced. The design includes a hydraulic rectifier to maintain one-way flow direction in order to obtain maximum power generation from the vertical oscillation of the suspension system and achieve handling and comfort car drive. A mathematical model is presented to study the system dynamics and non-linear effects for HPEHS system. A simulation model is created by using Advanced Modeling Environment Simulations software (AMEsim) to analyze system performance. Furthermore, a co-simulation platform model is developed using Matlab-Simulink and AMEsim to optimize the PID controller parameters of the external variable load resistor applied on the generator by using Particle Swarm Optimization (PSO).
Journal Article

Electrifying Long-Haul Freight—Part II: Assessment of the Battery Capacity

2019-01-25
Abstract Recently, electric heavy-duty tractor-trailers (EHDTTs) have assumed significance as they present an immediate solution to decarbonize the transportation sector. Hence, to illustrate the economic viability of electrifying the freight industry, a detailed numerical model to estimate the battery capacity for an EHDTT is proposed for a route between Washington, DC, to Knoxville, TN. This model incorporates the effects of the terrain, climate, vehicular forces, auxiliary loads, and payload in order to select the appropriate motor and optimize the battery capacity. Additionally, current and near-future battery chemistries are simulated in the model. Along with equations describing vehicular forces based on Newton’s second law of motion, the model utilizes the Hausmann and Depcik correlation to estimate the losses caused by the capacity offset of the batteries. Here, a Newton-Raphson iterative scheme determines the minimum battery capacity for the required state of charge.
Journal Article

Comparative Analysis of Performance of Neural Estimators for Diagnostics in Engine Emission System

2018-06-14
Abstract This article describes the results of a comparative performance analysis on the use of neural estimators to accurately estimate the Differential Pressure (DP) signal from diesel engine systems equipped with a Diesel Particulate Filter (DPF) aftertreatment system. For most systems, there are known and modeled relationships between system inputs and outputs; however, in the case of nonlinear, time-varying systems a detailed modeling of the system might not be readily available. Therefore, Artificial Neural Networks (ANNs) have been used for developing critical relationship between system inputs (engine and aftertreatment parameters) and system output (DP signal). Both batch (offline) and online learning ANN estimators have been proposed. A control-oriented engine out DPF-DP model is desirable for on-board applications as a virtual DPF-DP sensor which could be used in parallel as an alternate analytical redundancy-based sensor.
Journal Article

A Method for Turbocharging Single-Cylinder, Four-Stroke Engines

2018-07-24
Abstract Turbocharging can provide a low cost means for increasing the power output and fuel economy of an internal combustion engine. Currently, turbocharging is common in multi-cylinder engines, but due to the inconsistent nature of intake air flow, it is not commonly used in single-cylinder engines. In this article, we propose a novel method for turbocharging single-cylinder, four-stroke engines. Our method adds an air capacitor-an additional volume in series with the intake manifold, between the turbocharger compressor and the engine intake-to buffer the output from the turbocharger compressor and deliver pressurized air during the intake stroke. We analyzed the theoretical feasibility of air capacitor-based turbocharging for a single-cylinder engine, focusing on fill time, optimal volume, density gain, and thermal effects due to adiabatic compression of the intake air.
Journal Article

Transient Operation and Over-Dilution Mitigation for Low-Pressure EGR Systems in Spark-Ignition Engines

2018-09-17
Abstract Low-Pressure cooled Exhaust Gas Recirculation (LP-cEGR) is proven to be an effective technology for fuel efficiency improvement in turbocharged spark-ignition (SI) engines. Aiming to fully exploit the EGR benefits, new challenges are introduced that require more complex and robust control systems and strategies. One of the most important restrictions of LP-cEGR is the transient response, since long air-EGR flow paths introduce significant transport delays between the EGR valve and the cylinders. High dilution generally increases efficiency, but can lead to cycle-by-cycle combustion variation. Especially in SI engines, higher-than-requested EGR dilution may lead to combustion instabilities and misfires. Considering the long EGR evacuation period, one of the most challenging transient events is throttle tip-out, where the engine operation shifts from a high-load point with high dilution tolerance to a low-load point where EGR tolerance is significantly reduced.
Journal Article

Extending the Range of Data-Based Empirical Models Used for Diesel Engine Calibration by Using Physics to Transform Feature Space

2019-03-14
Abstract A new method that allows data-enabled (empirical) models, commonly used for automotive engine calibration, to extrapolate beyond the range of training data has been developed. This method used a physics-based system-level one-dimensional model to improve interpolation and allow extrapolation for three data-based algorithms, by modifying the model input (feature) space. Neural network, regression, and k-nearest neighbor predictions of engine emissions and volumetric efficiency were greatly improved by generating 736,281 artificial feature spaces and then performing feature selection to choose feature spaces (feature selection) so that extrapolations in the original feature space were interpolations in the new feature space. A novel feature selection method was developed that used a two-stage search process to uniquely select the best feature spaces for every prediction.
Journal Article

Lightweight Carbon Composite Chassis for Engine Start Lithium Batteries

2018-03-07
Abstract The supersession of metallic alloys with lightweight, high-strength composites is popular in the aircraft industry. However, aviation electronic enclosures for large format batteries and high power conversion electronics are still primarily made of aluminum alloys. These aluminum enclosures have attractive properties regrading structural integrity for the heavy internal parts, electromagnetic interference (EMI) suppression, electrical bonding for the internal cells, and/or electronics and failure containment. This paper details a lightweight carbon fiber composite chassis developed at Meggitt Sensing Systems (MSS) Securaplane, with a copper metallic mesh co-cured onto the internal surfaces resulting in a 50% reduction in weight when compared to its aluminum counterpart. In addition to significant weight reduction, it provides equal or improved performance with respect to EMI, structural and flammability performance.
Journal Article

Erosion Wear Response of Linz-Donawitz Slag Coatings: Parametric Appraisal and Prediction Using Imperialist Competitive Algorithm and Neural Computation

2019-03-14
Abstract Slag, generated from basic oxygen furnace (BOF) or Linz-Donawitz (LD) converter, is one of the recyclable wastes in an integrated steel plant. The present work aims at utilization of waste LD slag to develop surface coatings by plasma spraying technique. This study reveals that LD slag can be gainfully used as a cost-effective wear-resistant coating material. A prediction model based on an artificial neural network (ANN) is also proposed to predict the erosion performance of these coatings. The 2.27% error shows that ANN successfully predicts the erosion wear rate of the coatings both within and beyond the experimental domain. In addition to it, a novel optimization algorithm called imperialist competitive algorithm (ICA) is used to obtain minimum erosion wear rate of 12.12 mg/kg.
Journal Article

Mechanical Behavior of Representative Volume Element Specimens of Lithium-Ion Battery Modules without and with Electrolyte under Quasi-Static and Dynamic In-Plane Compressive Loading Conditions

2019-07-02
Abstract Small rectangular representative volume element (RVE) specimens of lithium-ion battery modules without and with electrolyte were tested under quasi-static and dynamic in-plane constrained compressive loading conditions. Effects of electrolyte and loading rate on the compressive behavior of RVE specimens were examined. The test results show that the average buckling stress of the specimens with electrolyte is higher than that of the specimens without electrolyte under both quasi-static and dynamic loading conditions. The test results also show that the average buckling stress of the specimens under dynamic loading conditions is higher than that of the specimens under quasi-static loading conditions, without or with the presence of electrolyte in the specimens. The percentage of increase of the average buckling stress of the specimens due to electrolyte under dynamic loading conditions is more than that of the specimens under quasi-static loading conditions.
Journal Article

A Bibliographical Review of Electrical Vehicles (xEVs) Standards

2018-04-18
Abstract This work puts presents an all-inclusive state of the art bibliographical review of all categories of electrified transportation (xEVs) standards, issued by the most important standardization organizations. Firstly, the current status for the standards by major organizations is presented followed by the graphical representation of the number of standards issued. The review then takes into consideration the interpretation of the xEVs standards developed by all the major standardization organizations across the globe. The standards are differentiated categorically to deliver a coherent view of the current status followed by the explanation of the core of these standards. The ISO, IEC, SAE, IEEE, UL, ESO, NTCAS, JARI, JIS and ARAI electrified transportation vehicles xEV Standards from USA, Europe, Japan, China and India were evaluated. A total approximated of 283 standards in the area have been issued.
Journal Article

Discussion on Charging Control Strategy for Power Battery at Low Temperatures

2017-10-08
Abstract In the case of electric vehicles, due to the charging current limitation of lithium battery at low temperatures (below -20°C), it has been proposed to heat the battery pack up to a suitable temperature range before charging through a liquid-heating plate with PTC. However, at a low state of charge (SOC), there is a question which one could take the place of battery pack to supply power for PTC when heating. So that off-board charger (OFC) has been considered to supply power for PTC in this paper. In order to control the current charging into the battery pack as less as possible at low temperatures, three control schemes of battery management system (BMS) are proposed and compared. Scheme 1: BMS controls the value of charging current request close to the working current of PTC. Scheme 2: BMS controls the value of charging voltage request to reach a state of relative balance. Scheme 3: BMS disconnects the pack from the charger and keeps the connection between PTC and charger.
Journal Article

Combined Battery Design Optimization and Energy Management of a Series Hybrid Military Truck

2018-10-31
Abstract This article investigates the fuel savings potential of a series hybrid military truck using a simultaneous battery pack design and powertrain supervisory control optimization algorithm. The design optimization refers to the sizing of the lithium-ion battery pack in the hybrid configuration. The powertrain supervisory control optimization determines the most efficient way to split the power demand between the battery pack and the engine. Despite the available design and control optimization techniques, a generalized mathematical formulation and solution approach for combined design and control optimization is still missing in the literature. This article intends to fill that void by proposing a unified framework to simultaneously optimize both the battery pack size and power split control sequence. This is achieved through a combination of genetic algorithm (GA) and Pontryagin’s minimum principle (PMP) where the design parameters are integrated into the Hamiltonian function.
Journal Article

Optimization Control for 4WIS Electric Vehicle Based on the Coincidence Degree of Wheel Steering Centers

2018-07-24
Abstract The steering centers of four wheels for passenger car do not coincide, which may result in tire wear and the unharmoniously movement of the vehicle. In this article, an optimization control method for Four Wheel Independent Steering (4WIS) electric vehicle based on the coincidence degree of steering centers is proposed, to improve the driving performance. The nonlinear vehicle model of the four-wheel independent steering vehicle is established, and the formula of the wheel steering center is derived. The coincidence degree of wheel steering centers is defined as the evaluation index, to describe and evaluate the performance of the coordination for wheels’ movement. Meanwhile, the structure design of 4WIS system and the establishment of Direct-Current (DC) steering motor model are carried out, and the Model Predictive Control (MPC) controller for steering actuator is designed.
Journal Article

Numerical and Experimental Investigation of the Optimization of Vehicle Speed and Inter-Vehicle Distance in an Automated Highway Car Platoon to Minimize Fuel Consumption

2018-06-22
Abstract The development of the technology of automated highways promises the opportunity for the vehicles to travel safely at a closer distance concerning each other. As such, vehicles moving in the wake of others experience a reduction in fuel consumption. This article investigates the effect of longitudinal distance between two passenger cars on drag coefficients numerically and experimentally. For the numerical analysis, the fluid flow at car speeds of 70, 90 and 110 km/h were examined. The Artificial Intelligence coding was applied to train an Artificial Neural Network to extend the calculated data. The optimum values for the inter-vehicle distance and the vehicle speed to assure the least drag coefficient are obtained. To support the numerical results an instrument designed and built particularly to accurately measure the fuel consumption was installed on a midsize sedan car and some field tests were carried out.
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