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Auburn Hills, MI, United States

Chrysler , officially FCA US LLC, is an American automobile manufacturer headquartered in Auburn Hills, Michigan and owned by Italian automaker Fiat. Chrysler is one of the "Big Three" American automobile manufacturers. It sells vehicles worldwide under its flagship Chrysler brand, as well as the Dodge, Jeep and Ram. Other major divisions include Mopar, its automotive parts and accessories division, and SRT, its performance automobile division. In 2014, FCA US LLC is the seventh biggest automaker in the world by production.The Chrysler Corporation was founded by Walter Chrysler in 1925, out of what remained of the Maxwell Motor Company. Chrysler greatly expanded in 1928, when it acquired the Fargo truck company and the Dodge Brothers Company and began selling vehicles under those brands; that same year it also established the Plymouth and DeSoto automobile brands.In the 1960s the company expanded into Europe, creating the Chrysler Europe division, formed from the acquisition of French, British and Spanish companies. In the 1970s, a number of factors including the 1973 oil crisis impacted Chrysler's sales, and by the late 1970s, Chrysler was on the verge of bankruptcy, forcing its retreat from Europe in 1979. Lee Iacocca was brought in as CEO and is credited with returning the company to profitability in the 1980s. In 1987, Chrysler acquired American Motors Corporation , which brought the profitable Jeep brand under the Chrysler umbrella.In 1998, Chrysler merged with German automaker Daimler-Benz AG to form DaimlerChrysler; the merger proved contentious with investors and Chrysler was sold to Cerberus Capital Management and renamed Chrysler LLC in 2007. Like the other Big Three automobile manufacturers, Chrysler was hit hard by the automotive industry crisis of 2008–2010.Through a combination of negotiations with creditors, filing for Chapter 11 bankruptcy reorganization on April 30, 2009, and participating in a bailout from the U.S. government through the T.A.R.P. program, Chrysler managed to remain in business. On June 10, 2009, Chrysler emerged from the bankruptcy proceedings with the United Auto Workers pension fund, Fiat S.p.A., and the U.S. and Canadian governments as principal owners. The bankruptcy resulted in Chrysler defaulting on over $4 billion in debts. By May 24, 2011, Chrysler finished repaying its obligations to the U.S. government five years early, although the cost to the American taxpayer was $1.3 billion. Over the next few years Fiat gradually acquired the other parties' shares while removing much of the weight of the loans in a short period. On January 1, 2014, Fiat S.p.A announced a deal to purchase the rest of Chrysler from the United Auto Workers retiree health trust. The deal was completed on January 21, 2014, making Chrysler Group a subsidiary of Fiat S.p.A. In May 2014, Fiat Chrysler Automobiles, NV was born by merging Fiat S.p.A. into the company. This was completed in August 2014. Chrysler Group LLC remained a subsidiary until December 15 2014, when it was renamed FCA US LLC, to reflect the Fiat-Chrysler merger. Wikipedia.

Cao J.,Illinois Institute of Technology | Cao J.,Chrysler Group LLC | Emadi A.,Illinois Institute of Technology | Emadi A.,McMaster University
IEEE Transactions on Power Electronics | Year: 2012

In this paper, a new battery/ultracapacitor hybrid energy storage system (HESS) is proposed for electric drive vehicles including electric, hybrid electric, and plug-in hybrid electric vehicles. Compared to the conventional HESS design, which uses a larger dc/dc converter to interface between the ultracapacitor and the battery/dc link to satisfy the real-time peak power demands, the proposed design uses a much smaller dc/dc converter working as a controlled energy pump to maintain the voltage of the ultracapacitor at a value higher than the battery voltage for the most city driving conditions. The battery will only provide power directly when the ultracapacitor voltage drops below the battery voltage. Therefore, a relatively constant load profile is created for the battery. In addition, the battery is not used to directly harvest energy from the regenerative braking; thus, the battery is isolated from frequent charges, which will increase the life of the battery. Simulation and experimental results are presented to verify the proposed system. © 2011 IEEE. Source

Shamsaei N.,Chrysler Group LLC | Fatemi A.,University of Toledo
International Journal of Fatigue | Year: 2014

A significant portion of the fatigue life is typically spent in growth of small cracks. In addition, the stress state in many structures and components is multiaxial. Therefore, the study of small crack growth behaviour with regards to its growth path as well as growth rate under combined stresses can be of great importance in many applications. This study investigates small crack growth behaviour of several steels under multiaxial states of stress. Experimental observations from solid and thin-walled tubular round specimens under various multiaxial cyclic loadings including in-phase and out-of-phase, tension-torsion and tension-tension, and with or without mean stresses are used to characterise small crack growth behaviour. The steels used include 1045 and 1050 medium carbon steels, 304L stainless steel, and Inconel 718. Effects of load non-proportionality, mean stresses, and friction-induced closure on small fatigue crack growth behaviour are discussed. Critical plane analysis and an effective strain intensity factor are used to predict crack growth path as well as to correlate crack growth rates under various combined stress conditions. © 2013 Elsevier Ltd. All rights reserved. Source

Wirasingha S.G.,Chrysler Group LLC | Emadi A.,Illinois Institute of Technology
IEEE Transactions on Vehicular Technology | Year: 2011

To reduce fuel consumption and emissions in plug-in hybrid electric vehicles (PHEVs), it is equally important to select an appropriate drive train topology as it is to develop a suitable power flow control strategy. While there are many control strategies that have been developed and presented, most are expansions of hybrid electric vehicle (HEV) control strategies and do not maximize the true potential the PHEV offers as a result of its ability to operate in electric-only mode over a significant distance. In this paper, state-of-the-art control strategies are reviewed and classified in detail. PHEV controllers mostly operate on either a rule-based or an optimization-based algorithm, each having its own advantages and disadvantages. An overview of the controllers is given, and an analysis on which strategy is more suitable to maximize PHEV performance in different drive cycle conditions is provided. Finally, a new classification for PHEV control strategies based on the operation of the vehicle is presented and verified through simulation results. © 2010 IEEE. Source

Wirasingha S.G.,Chrysler Group LLC | Gremban R.,California Cars Initiative | Emadi A.,McMaster University
IEEE Transactions on Smart Grid | Year: 2012

Many alternative fuel vehicle technologies, including plug-in hybrid electric vehicles (PHEVs), are currently being developed. Among the key reasons for their development is the increasing demand for fuel, which has resulted in increased fuel costs and brought attention to resource limitations. Fuel is also directly related to emissions and there is a conscious effort to minimize the environmental impact of vehicles. When evaluating the operational success of these technologies, it is important to consider the energy cycle of the vehicle. Source-to-wheel (STW) efficiency and emissions analysis is proposed in this paper to provide a value for comparing current and proposed vehicle technologies. The STW cycle includes the raw material production stage, transportation and storage stages of energy sources, energy transportation/ storage/distribution stage, and finally the vehicle operations stage. The STW calculation is divided into two sections for ease of analysis. They are the cycle from the source of the energy to the vehicle and the cycle from when the energy is delivered to the vehicle to the work done at the wheels. They are referred to as the source-to-vehicle (STV) and vehicle-to-wheel (VTW) cycles, respectively. The impact of the vehicle manufacturing stage on this analysis will be addressed and the different approaches to integrating PHEVs into the current fleet of vehicles will also be discussed. © 2011 IEEE. Source

The common practice in finite element based fatigue calculation with multiple channels of road load is to perform a set of unit load static stress analysis and conduct stress time history construction later during fatigue calculation. The main advantage of this so-called quasi-static finite element based fatigue calculation is to avoid time-consuming dynamic stress analysis and also reduce static stress analysis from millions of real load cases to a few dozens unit-load cases. The main disadvantage of this quasi-static finite element based fatigue calculation is the absence of vibration-induced stresses in stress time history construction and fatigue analysis. A decade ago, a modal transient finite element based fatigue calculation was proposed to introduce vibration-induced stresses into finite element based fatigue calculation. The idea is to add vibration-induced modal stresses to load-induced instant stresses in stress time history construction and fatigue calculation. But a time consuming modal transient dynamic analysis has to be conducted in generating modal coefficient time histories. This paper will introduce a new approach to include vibration stress in fatigue calculation without requiring any dynamic analysis. The concept is to have some critical acceleration data, acquired with load data during road load data acquisition, and convert the acquired acceleration data into additional operating loads for stress time history construction and fatigue calculation. This paper will present two steering linkage system prototype vibration fatigue case studies and demonstrate fatigue life calculation accuracy from this new d'Alembert's principle finite element based fatigue calculation. Copyright © 2013 SAE International. Source

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