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2016-11-22
Event
2016-10-25
Event
2016-10-24
Event
Separate sub-sessions cover powertrain control, calibration, and system-level optimization processes related to achieving stringent market fuel economy, emissions, performance, reliability, and quality demands. Topics include the control, calibration, and diagnostics of the engine, powertrain, and supporting electromechanical subsystems related to energy management in conventional and hybrid operation, considering the simultaneous optimization of hardware design parameters and control software calibration parameters.
2016-10-24
Event
The success of HEV's, PHEV's & EV's is highly dependent on their batteries. This session focuses on advanced battery technologies, including, but not limited to: advanced materials and cell chemistries, battery management systems and controls, modeling, testing, diagnosis and health monitoring, safety, reliability, durability, battery charging, battery economics/cost reduction, and system integration/optimization. These topics can be addressed at the cell, module, pack or vehicle levels.
2016-09-27
Event
2016-08-23
Event
2016-07-26
Event
2016-06-28
Event
2016-05-24
Event
2016-05-02 ...
  • May 2-3, 2016 (8:30 a.m. - 4:30 p.m.) - Troy, Michigan
  • November 17-18, 2016 (8:30 a.m. - 4:30 p.m.) - Troy, Michigan
Training / Education Classroom Seminars
Driven by the need for lower emissions, better fuel economy and higher efficiency, hybrid vehicles are appearing in many different configurations on today's roadways. While the powertrain components such as the drive motor, motor controller and cooling system are somewhat familiar to the automotive industry, the battery systems are a relatively unfamiliar aspect. This seminar will introduce participants to the concepts of hybrid vehicles, their missions and the role of batteries in fulfilling those requirements.
2016-05-01
Journal Article
2015-01-9145
Abdullah AL-Refai, Osamah Rawashdeh, Rami Abousleiman
Abstract Lithium-Ion batteries are the standard portable power solution to many consumers and industrial applications. These batteries are commonly used in laptop computers, heavy duty devices, unmanned vehicles, electric and hybrid vehicles, cell phones, and many other applications. Charging these batteries is a delicate process because it depends on numerous factors such as temperature, cell capacity, and, most importantly, the power and energy limits of the battery cells. Charging capacity, charging time and battery pack temperature variations are highly dependent on the charging method used. These three factors can be of special importance in applications with strict charging time requirements or with limited thermal management capabilities. In this paper, three common charging methods are experimentally studied and analyzed. Constant-current constant-voltage, the time pulsed charging method, and the multistage constant current charging methods were considered.
2016-05-01
Journal Article
2015-01-9147
Zhiyun Zhang, Miaohua Huang, Yupu Chen, Shuanglong Zhu
Abstract In the field of Electric Vehicle (EV), what the driver is most concerned with is that whether the value of the battery's capacity is less than the failure threshold because of the degradation. And the failure threshold means instability of the battery, which is of great danger for drives and passengers. So the capacity is an important indicator to monitor the state of health (SOH) of the battery. In laboratory environment, standard performance tests can be carried out to collect a number of related data, which are available for regression prediction in practical application, such as the on-board battery pack. Firstly, we make use of the NASA battery data set to form the observed data sequence for regression prediction. And a practical method is proposed to determine the minimum embedding dimension and get the recurrence formula, with which a capacity model is built.
2016-05-01
Journal Article
2015-01-9148
Saeed Asgari, Shailendra Kaushik
Abstract A linear parameter varying (LPV) reduced order model (ROM) is used to approximate the volume-averaged temperature of battery cells in one of the modules of the battery pack with varying mass flow rate of cooling fluid using uniform heat source as inputs. The ROM runs orders of magnitude faster than the original CFD model. To reduce the time it takes to generate training data, used in building LPV ROM, a divide-and-conquer approach is introduced. This is done by dividing the battery module into a series of mid-cell and end-cell units. A mid-cell unit is composed of a cooling channel sandwiched in between two half -cells. A half-cell has half as much heat capacity as a full-cell. An end-cell unit is composed of a cooling channel sandwiched in between full-cell and a half-cell. A mass flow rate distribution look-up-table is generated from a set of steady-state simulations obtained by running the full CFD model at different inlet manifold mass flow rate samples.
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