Smart charging and anti-idling systems /
By: Huang, Yanjun (Mechanical engineer) [author.].
Contributor(s): Fard, Soheil Mohagheghi [author.] | Khazraee, Milad [author.] | Wang, Hong (Engineer) [author.] | Khajepour, Amir [author.].
Material type: BookSeries: Synthesis digital library of engineering and computer science: ; Synthesis lectures on advances in automotive technology: # 4.Publisher: [San Rafael, California] : Morgan & Claypool, 2018.Description: 1 PDF (viii, 81 pages) : illustrations.Content type: text Media type: electronic Carrier type: online resourceISBN: 9781681733647.Subject(s): Motor vehicles -- Batteries | Battery chargers | Motor vehicles -- Motors -- Exhaust systems | Motor vehicles -- Electric equipment | anti-idling system | auxiliary-system electrification | power train modeling and sizing | working-condition prediction | power management strategies | dynamic programming | AECMS (adaptive equivalent fuel consumption minimization strategy) | model predictive controlDDC classification: 629.254 Online resources: Abstract with links to resource Also available in print.Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
---|---|---|---|---|---|---|
E books | PK Kelkar Library, IIT Kanpur | Available | EBKE801 |
Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader.
Part of: Synthesis digital library of engineering and computer science.
Includes bibliographical references (pages 71-77).
1. Introduction -- 1.1 Motivation -- 1.2 Review of anti-idling products -- 1.2.1 Mobile products -- 1.2.2 Stationary products -- 1.3 Summary --
2. Powertrain modeling and component sizing for the smart charger -- 2.1 Modeling -- 2.1.1 Vehicle longitudinal dynamics -- 2.1.2 Generator modeling -- 2.1.3 Battery modeling -- 2.1.4 Engine modeling -- 2.2 Design optimization -- 2.2.1 Optimization algorithm structure -- 2.2.2 Objective cost function -- 2.2.3 Optimization constraints -- 2.3 Design optimization -- 2.4 Summary --
3. Driving and service cycle estimation -- 3.1 Prediction of the auxiliary load in service vehicles -- 3.2 Driving information estimation -- 3.3 Summary --
4. Power management controller design for the smart charger -- 4.1 Two-level DP-adaptive ECMS power management controller -- 4.1.1 High-level controller -- 4.1.2 Lower-level controller -- 4.1.3 Case study -- 4.2 The MPC-based power management controller -- 4.2.1 Prescient MPC -- 4.2.2 Average-concept based MPC -- 4.3 Summary --
5. Conclusions -- References -- Authors' biographies.
Abstract freely available; full-text restricted to subscribers or individual document purchasers.
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As public attention on energy conservation and emission reduction has increased in recent years, engine idling has become a growing concern due to its low efficiency and high emissions. Service vehicles equipped with auxiliary systems, such as refrigeration, air conditioning, PCs, and electronics, usually have to idle to power them. The number of service vehicles (e.g. public-school tour buses, delivery-refrigerator trucks, police cars, ambulances, armed vehicles, firefighter vehicles) is increasing significantly with tremendous social development. Therefore, introducing new anti-idling solutions is inevitably vital for controlling energy unsustainability and poor air quality. There are a few books about the idling disadvantages and anti-idling solutions. Most of them are more concerned with different anti-idling technologies and their effects on the society rather than elaborating an anti-idling system design considering different applications and limitations. There is still much room to improve existing anti-idling technologies and products. In this book, we took a service vehicle, refrigerator truck, as an example to demonstrate the whole process of designing, optimizing, controlling, and developing a smart charging system for the anti-idling purpose. The proposed system cannot only electrify the auxiliary systems to achieve anti-idling, but also utilize the concepts of regenerative braking and optimal charging strategy to arrive at an optimum solution. Necessary tools, algorithms, and methods are illustrated and the benefits of the optimal anti-idling solution are evaluated.
Also available in print.
Title from PDF title page (viewed on June 23, 2018).
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