Design and Analysis of Hydraulic Hybrid Passenger Vehicles

University of Minnesota Ph.D. dissertation. September 2015. Major: Mechanical Engineering. Advisors: Perry Li, Thomas Chase. 1 computer file (PDF); x, 305 pages.The research described in this dissertation focuses on the development of computationally efficient design methodology to optimize the hydraulic hybrid power-split transmission for fuel efficiency, acceleration performance and robustness against powertrain uncertainties. This research also involve experimental implementation of a three-level hierarchical control approach on two test beds, requiring powertrain control design and fine-tuning. Hybrid powertrains have the potential to benefit the fuel efficiency of highway and off-highway vehicles. Hydraulic hybrid has high power density. Hydraulic power-split architecture is chosen in this study for its flexibility in operation and combined advantage of series and parallel architecture. An approach for optimizing the configuration and sizing of a hydraulic hybrid power-split transmission is proposed. Instead of considering each mechanical configuration consisting of combinations of gear ratios, a generalized kinematic relation is used to avoid redundant computation. The Lagrange multiplier method for computing the optimal energy management control is shown to be 450 times more computationally efficient for use in transmission design iterations. To exploit the benefit of high power density of hydraulics, a classical multi-objective solver is utilized to incorporate the acceleration performance criteria into the transmission design optimization. By considering worst-case uncertainty, the transmission design is optimized to be robust against powertrain uncertainties and insensitive to operating condition variations, and yet fuel efficient. The Generation I and II vehicles are experimental platforms built to implement controls and to validate the fuel efficiency gain for power-split transmission. The powertrain for the platforms are modeled to predict the potential fuel efficiency improvement by different energy management strategies. Results show maximum of 74\% fuel efficiency gain by optimizing engine management from CVT to full optimal hybrid operation. The three-level control strategy is implemented on the Generation I vehicle. This control strategy segregates the tasks of the drive-train into three layers that respectively 1) manages the accumulator energy storage (high level); 2) performs vehicle level optimization (mid-level); and 3) attains the desired vehicle operating condition (low level). Results validated the modularity and effectiveness of this control structure

System and Thermal Modeling of Hydraulic Hybrids: Thermal Characteristics Analysis

Hybrid vehicles have become a popular alternative to conventional powertrain architectures by offering improved fuel efficiency along with various other environmental benefits. Among them, hydraulic hybrid vehicles (HHVs) have several benefits, which make it the superior technology for certain applications over other types of hybrid vehicles, such as lower component costs, more environmentally friendly construction materials, higher power densities, and more regenerative energy available from braking. There have been various studies on HHVs, such as energy management optimization, control strategies for various system configurations, the effect of system parameters on the hybrid system, and proposals for novel hybrid architectures. One area not been thoroughly covered in the past is a detailed modeling and examination of the thermal characteristics for HHVs due to a difficulty of describing the rapid thermal transients in the unsteady state systems. In this dissertation, a comprehensive system and thermal modeling has been studied for hydraulic hybrid transmissions (HHTs). The main motivation behind developing a thermal model of HHTs is to gain a deeper understanding of the system’s thermal performance, and key influencing factors, without relying on experimental data. This will enable HHVs to be designed more efficiently by identifying and addressing potential issues with transmission’s thermal performance prior to hardware testing. Since there exists no thermal study on HHVs in the past, a thermal modeling method has been introduced, which can be applicable to hydraulic hybrid architectures. A thermal modeling methodology based on a novel numerical scheme and accurate theoretical description has been developed in order to capture the rapid thermal transient in the hydraulic system under unsteady state conditions. The model has been applied to a series HHT and validated with measured data from the hardware-in-the-loop (HIL) test rig with a standard driving cycle, FTP-72. In addition, the proposed thermal modeling methodology has been used to analyze and optimize the cooling system of a novel HHV architecture, which is implemented in a sport utility vehicle (SUV) in Maha Fluid Power Research Center. The modeling results have been compared with the measured data while driving the vehicle. In both studies, the simulation results have shown a good correlation with the experimental data in terms of the overall trends and variation ranges. The goal of the developed model is the application to the system and thermal issues in HHVs, such as thermal stability analysis, management of the cooling system, packaging and hydraulic component optimization, and evaluation of thermal characteristics of different architectures. As an advanced topic of this research, thermal management of an open and a closed circuit hydraulic hybrid systems has been studied by simulation. The comparison results show a potential to a better thermal management for the open circuit systems with smaller heat exchangers, as well as less power consumption with incorporation of smaller charge pumps compared to the closed circuit systems. In the future, the developed comprehensive system and thermal modeling method can be applied to different advanced topics, such as analysis of performance and thermal characteristics, systems and components optimization, and systems evaluation with different external conditions, for different hydraulic hybrid systems

Multiobjective Optimization of the Power Flow Control of Hybrid Electric Power Train Systems within Simulation and Experimental Emulation Applications

In this thesis, the power flow control of hybrid electric power train systems is discussed using the focus of multiobjective optimization goals and related algorithms, based on different control optimization methods, are developed and applied within simulation and experimental environments. Based on the basic relations of hybrid power train systems, an improved technique for the experimental realization and evaluation of these systems is developed and the related Hardware-in-the-Loop (HiL) hybrid electric power train emulation system is demonstrated. Hereby, it is shown that this emulation system technique is suitable to be applied for a more generalized view of the power train structures (consideration of the components as power sources, sinks, transmission elements, storage elements etc.) and its power flow control. The principal applicability of the system is demonstrated using the example of a hybrid electric vehicle as well as other system technologies such as hybrid hydraulic power trains and wind energy conversion systems. The core of the thesis is the discussion, development, application, and evaluation of power flow control optimization algorithms. Hereby, the considered power flow control techniques of the power train are realized with respect to a multiobjective framework using the example of drivability, fuel economy, and component life time as system requirements to be optimized during the operation. From this requirements, a multiobjective control optimization problem results consisting of a suitable combination of the known control goals power management, energy management, and lifetime management is realized. After a discussion about the principal influences of the power flow control on the different performance properties, the application of different control optimization techniques is discussed. Hereby, the example of a fuel cell/supercapacitor-based hybrid electric power train system including braking energy recovery is used. As control optimization methods, parameter optimization techniques are applied at first. Hereby, an embedded-online optimization based on a Golden Section search and an offline optimization based on Global Optimation methods are discussed and applied. Furthermore, direct optimization techniques based on Dynamic Programming (DP) and Model Predictive Control (MPC) are realized. Subsequently, an Instantaneous Optimality (IO)-based technique, which consists of a lookup table-based Time-Invariant Feedback Controller technique, is developed. It becomes clear that all methods leads to suitable results and significant improvement of the control performance. A concluding overview of the methods and its strengths and weaknesses dependent on the application is provided.In dieser Arbeit wird die Leistungsflussregelung bei hybridelektrischen Antriebssystemen mit dem Schwerpunkt der Mehrkriterienoptimierung diskutiert. Hierbei werden geeignete Algorithmen, basierend auf verschiedenen Stellgrößenoptimierungsmethoden, entwickelt und in Simulationen sowie in experimentellem Umfeld angewendet. Aufbauend auf die Grundzusammenhänge hybrider Antriebssysteme wird eine weiterentwickelte experimentelle Umgebung zur Untersuchung und Bewertung vorgestellt und der entsprechende Hardware-in-the-Loop (HiL)-Versuchsstand zur Emulation entsprechender Systeme demonstriert. Diese Emulationstechnik erlaubt eine generalisierte Betrachtung von Antriebssystemstrukturen (Betrachtung der Komponenten als Quellen, Senken, Übertragungselemente, Speicher etc.) und der entsprechenden Leistungsflussregelung. Den Hauptteil dieser Arbeit bildet die Diskussion sowie die Entwicklung, Anwendung und Bewertung von Algorithmen zur Optimierung der Leistungsflussregelung hybridelektrischer Antriebssysteme. In diesem Zusammenhang erfolgt eine mehrkriterielle Betrachtung und Bewertung des Antriebssystems in Hinblick auf die Dynamik, die Kraftstoffökonomie und die Komponentenlebensdauer. Das hieraus resultierende mehrkriterielle Optimierungsproblem der Stellgrößenfolge kann hierbei als Überlagerung von Leistungs-, Energie- und Lebensdauermanagement aufgefasst werden. Basierend auf den Haupteinflüssen der Leistungsflussregelungen auf verschiedene Systemeigenschaften erfolgt die Entwicklung, Anwendung, Bewertung und Diskussion verschiedener Stellgrößenoptimierungsmethoden und -algorithmen. Diese werden am Beispiel eines Brennstoffzellen/Supercap-basierten hybridelektrischen Antriebssystems mit Bremsenergierekuperation demonstriert. Zur Optimierung der Leistungsflussregelung werden als erstes Parameteroptimierungstechniken vorgestellt, wobei eine Embedded-online-Optimierung basierend auf der Methode des Goldenen Schnitts sowie eine Offline-Optimierung unter Verwendung von globalen Optimierungsalgorithmen diskutiert und angewendet werden. Nachfolgend werden direkte Stellgrößenoptimierungstechniken vorgestellt, wobei die Verfahren der Dynamischen Programmierung und des Modelprädiktiven Reglers realisiert werden. Abschließend wird die Entwicklung und Anwendung eines Algorithmus basierend auf der momentanen Optimalität (Instantaneous Optimality) diskutiert, welcher aus einem kombinierten Geschwindigkeits-Prädiktionsalgorithmus und vordefinierten Kennfeldern für die Regelung besteht. Die verwendeten Methoden werden vergleichend gegenübergestellt und gemäß ihrer Stärken und Schwächen bewertet

Energy Efficient Control of Hydrostatic Drive Transmissions: A Nonlinear Model-Based Approach

The high standard of living in industrial countries is based on the utilization of machines. In particular, the tasks performed with hydraulic work machines (HWMs) are essential in numerous industrial fields. Agriculture, mining, and construction are just a few examples of the lines of business that would be inconceivable today without HWMs. However, rising oil prices and competing technologies are challenging the manufacturers of these machines to improve their fuel economy.Despite the fact that energy efficiency research of hydraulic systems has been active for more than a decade, there seems to be a significant gap between industry and academia. The manufacturers of HWMs have not adopted, for example, novel system layouts, prototype components, or algorithms that require powerful control units in their products.The fuel economy of HWMs can be increased by utilizing system information in control algorithms. This cost-effective improvement enables operation in challenging regions and closer to the operating boundaries of the system. Consequently, the information about the system has to be accurate. For example, reducing the rotational speed of the engine has proven effective in improving the energy efficiency, but it increases the risk of even stalling the engine, for instance in situations where the power generation cannot meet the high transient demand. If this is considered in the controller with low uncertainty, fuel economy can be improved without decreasing the functionality of the machine.This thesis studies the advantages of model-based control in the improvement of the fuel economy of HWMs. The focus is on hydrostatic drive transmissions, which is the main consumer of energy in certain applications, such as wheel loaders.We started by developing an instantaneous optimization algorithm based on a quasi-static system model. The control commands of this fuel optimal controller (FOC) were determined based on cost function, which includes terms for fuel economy, steady-state velocity error, and changes in the control commands.Although the use of quasi-static models is adequate for steady-state situations, the velocity tracking during transients and under load changes has proven to be inadequate. To address this issue, a high-performance velocity-tracking controller was devised. Full state feedback was assumed, and we resorted to a so-called D-implementation, which eliminates, for example, the need for the equilibrium values of pressure signals. The nonlinearities of the system were considered with the state-dependent parameters of the linear model.In the next step, a nonlinear model predictive controller combined fuel economy control and velocity tracking. To the best of the author’s knowledge, this is the first time that the model predictive control scheme has been utilized with such a detailed system model that also considers the hydraulic efficiencies and torque generation of the engine. This enables utilizing the controller as a benchmark of control algorithms for non-hybrid hydrostatic drive transmissions that do not require information about the future.The initial tests of all the controllers were conducted with a validated simulation model of a research platform machine, a five-ton municipal tractor. In addition, the FOC and velocity-tracking controller were implemented into the control system of the machine. The practical worth of the FOC was proven with a relatively unique field experiment set-up that included, for example, an online measurement system of fuel consumption and autonomous path following. The fuel economy improved up to 16.6% when compared with an industrial baseline controller. The devised velocity-tracking concept was also proven as a significant reduction of error was observed in comparison with classic literature solutions, namely state feedback and proportional-integral-derivative controllers

Chapter 34 - Biocompatibility of nanocellulose: Emerging biomedical applications

Nanocellulose already proved to be a highly relevant material for biomedical applications, ensued by its outstanding mechanical properties and, more importantly, its biocompatibility. Nevertheless, despite their previous intensive research, a notable number of emerging applications are still being developed. Interestingly, this drive is not solely based on the nanocellulose features, but also heavily dependent on sustainability. The three core nanocelluloses encompass cellulose nanocrystals (CNCs), cellulose nanofibrils (CNFs), and bacterial nanocellulose (BNC). All these different types of nanocellulose display highly interesting biomedical properties per se, after modification and when used in composite formulations. Novel applications that use nanocellulose includewell-known areas, namely, wound dressings, implants, indwelling medical devices, scaffolds, and novel printed scaffolds. Their cytotoxicity and biocompatibility using recent methodologies are thoroughly analyzed to reinforce their near future applicability. By analyzing the pristine core nanocellulose, none display cytotoxicity. However, CNF has the highest potential to fail long-term biocompatibility since it tends to trigger inflammation. On the other hand, neverdried BNC displays a remarkable biocompatibility. Despite this, all nanocelluloses clearly represent a flag bearer of future superior biomaterials, being elite materials in the urgent replacement of our petrochemical dependence

Enhancing Future Skills and Entrepreneurship

This open access book presents the proceedings of the 3rd Indo-German Conference on Sustainability in Engineering held at Birla Institute of Technology and Science, Pilani, India, on September 16–17, 2019. Intended to foster the synergies between research and education, the conference is one of the joint activities of the BITS Pilani and TU Braunschweig conducted under the auspices of Indo-German Center for Sustainable Manufacturing, established in 2009. The book is divided into three sections: engineering, education and entrepreneurship, covering a range of topics, such as renewable energy forecasting, design & simulation, Industry 4.0, and soft & intelligent sensors for energy efficiency. It also includes case studies on lean and green manufacturing, and life cycle analysis of ceramic products, as well as papers on teaching/learning methods based on the use of learning factories to improve students’problem-solving and personal skills. Moreover, the book discusses high-tech ideas to help the large number of unemployed engineering graduates looking for jobs become tech entrepreneurs. Given its broad scope, it will appeal to academics and industry professionals alike

Pacing with restoration of respiratory sinus arrhythmia improved cardiac contractility and the left ventricular output: a translational study

Introduction: Respiratory sinus arrhythmia (RSA) is a prognostic value for patients with heart failure and is defined as a beat-to-beat variation of the timing between the heart beats. Patients with heart failure or patients with permanent cardiac pacing might benefit from restoration of RSA. The aim of this translational, proof-of-principle study was to evaluate the effect of pacing with or without restored RSAon parameters of LV cardiac contractility and the cardiac output

Recent Development of Hybrid Renewable Energy Systems

Abstract: The use of renewable energies continues to increase. However, the energy obtained from renewable resources is variable over time. The amount of energy produced from the renewable energy sources (RES) over time depends on the meteorological conditions of the region chosen, the season, the relief, etc. So, variable power and nonguaranteed energy produced by renewable sources implies intermittence of the grid. The key lies in supply sources integrated to a hybrid system (HS)