Modeling the Thermal Behavior of Internal Combustion in Hybrid Electric Vehicles With and Without Exhaust Gas Heat Recirculation

2012 ◽  
Author(s):  
Teresa Donateo ◽  
Damiano Pacella
Keyword(s):  
Thermal Behavior ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Gasoline Engine ◽  
Operating Conditions ◽  
Lumped Parameter Model ◽  
Exhaust Gas ◽  
Exhaust Gases ◽  
Heat Recirculation ◽  
Hybrid Electric

A first-order lumped-parameter model for the prediction of thermal behavior of a single-cylinder gasoline engine for Hybrid Electric Vehicles (HEVs) has been implemented. The model is coupled with a zero-dimension in-cylinder model that evaluates the working cycle of the engine according to the actual operating conditions and calculates the temperature of the exhaust gases, the overall efficiency of the engine and the exhaust gases flow rate. The model takes into account the possibility of using exhaust gas heat recirculation in order to enhance engine warm-up during cold start which improves its efficiency. The supervisory strategy takes into account not only predicted speed and ambient and road conditions along a future time window but also actual battery state of the charge and engine temperature to select the optimal power split between the ICE-generator group and the batteries. The proposed model represents an improvement with respect to a previous investigation of the authors where the temperature of the engine were assumed to increase/decrease of on Celsius degree in each seconds according to the state of the engine (ON/OFF).

Analysis of Li-Ion Battery Characteristics and Thermal Behavior

2013 ◽  
Author(s):  
Krishnashis Chatterjee ◽  
Pradip Majumdar ◽  
David Schroeder ◽  
S. Rao Kilaparti
Keyword(s):  
Thermal Behavior ◽  
Lithium Ion Batteries ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Internal Heat ◽  
Lithium Ion ◽  
Test Facility ◽  
Transportation Industry ◽  
Ambient Temperatures ◽  
Hybrid Electric

Development of electric and hybrid electric vehicles is of great interest to the transportation industry due to increased demand and cost of imported fuel, uncertainty in the steady supply of oil, and increased standards for reduced emissions. Lithium-ion batteries are considered as one of the leading types for the battery systems to be employed in electric vehicles (EVs) or hybrid electric vehicles (HEVs). Using a regenerative braking system and storing it in battery stacks and using it later for propulsion and acceleration can improve the overall efficiency and reduction of fuel consumption. The objective of this study is to evaluate experimentally the battery performance considering different discharge and charge rates, and investigate the thermal behavior and thermal management requirements of the batteries under a variety of environmental conditions. An experimental test facility has been developed to evaluate thermal performance during charging and discharging modes. Environmental temperatures were varied in environmental chamber to analyze their effects on the charging and discharging patterns of the battery by using the CADEX battery analyzer in order to find the temperature range for optimum battery performance. The batteries were monitored with thermal sensors and a thermal imaging camera while they were run through different load scenarios. In the present study, lithium-ion batteries have been tested and battery performance in terms of polarization curves and discharge capacity were measured using a computerized battery analyzer system for different discharge and charge rates, and over a range of ambient temperatures. Results indicate that at higher discharge and charge rates battery performance decreases due to increased polarization losses, which results in increased internal heat generation and temperature of the battery. Battery performance also depends strongly on the ambient temperature conditions.

scholarly journals Lifetime Model Development for Integration in Power Management of HEVs By Terms of Minimizing Fuel Consumption and Battery Degradation

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Nejra Beganovic ◽  
Bedatri Moulik ◽  
Ahmed Mohamed Ali ◽  
Dirk S¨offker
Keyword(s):  
Fuel Consumption ◽  
Power Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Operating Conditions ◽  
Battery Lifetime ◽  
Conflicting Objectives ◽  
Battery Degradation ◽  
Lifetime Model ◽  
Hybrid Electric

Along with increasingly frequent use of electric and hybrid electric vehicles, the constraints and demands placed on the them become stricter. The most noticeable challenge considering Hybrid Electric Vehicles (HEVs) is to provide an optimalpower flow between multiple electric sources alongside provided as less as possible aging of energy storage components. To provide efficient battery usage with respect to batteries lifetime, it becomes unavoidable to develop battery lifetime models, which do not only reflect the State-of-Heath (SoH) but also allow battery lifetime prediction. The lifetimeoriented battery models have to be integrated in power management. To be used efficiently and to provide optimal power split ensuring mitigation of battery degradation without sacrificing desired power consumption, accurate modeling of battery degradation is of utmost importance. This implies that gradual battery degradation, which is directly affected by applied loading profiles, has to be monitored and used as additional control input. Moreover, the lifetime model developed in this case has to provide model outputs also in the timeframe of power management. In this contribution, a machine state-based lifetime model for electric battery source is developed. In this particular case, different degradation states as well as machine state transitions are identified in accordance to current operating conditions. Here, the change in charging/ discharging rate (C-rate), overcharging/undercharging of the battery (depth-of-discharge), and the temperature are taken in consideration to define machine model states. The End-of-Lifetime (EoL) is defined as deviation between nominal and current ampere-hour (Ah)-throughput. The proposed machine state-based lifetime model is verified based on existing battery lifetime models using simulation setup. The developed lifetime model in this way serve as a prerequisite forits integration into power management with an aim to provide the trade-off between aforementioned conflicting objectives; fuel consumption and battery degradation.

Thermal Behavior of Two Commercial Li-Ion Batteries for Plug-in Hybrid Electric Vehicles

2014 ◽  
Author(s):  
Ehsan Samadani ◽  
Leo Gimenez ◽  
William Scott ◽  
Siamak Farhad ◽  
Michael Fowler ◽  
...  
Keyword(s):  
Thermal Behavior ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Li Ion Batteries ◽  
Li Ion ◽  
Hybrid Electric

Development of Evaluation System for Exhaust Gas and Fuel Economy of Next-generation Hybrid Electric Vehicles

2013 ◽  
Author(s):  
Nobunori Okui ◽  
Terunao Kawai ◽  
Tetsuya Niikuni ◽  
Masahiko Suzuki ◽  
Hiroshi Takahata ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Fuel Economy ◽  
Evaluation System ◽  
Hybrid Electric Vehicles ◽  
Exhaust Gas ◽  
Next Generation ◽  
Hybrid Electric ◽  
Generation Hybrid

scholarly journals Analytical Modeling and Comparison of Two Consequent-Pole Magnetic-Geared Machines for Hybrid Electric Vehicles

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1888 ◽  
Author(s):  
Hang Zhao ◽  
Chunhua Liu ◽  
Zaixin Song ◽  
Jincheng Yu
Keyword(s):  
Mathematical Modeling ◽  
Electric Vehicles ◽  
Analytical Modeling ◽  
Hybrid Electric Vehicles ◽  
Electric Machines ◽  
Modeling Method ◽  
Operating Conditions ◽  
Hybrid Electric ◽  
Consequent Pole ◽  
Two Machines

The exact mathematical modeling of electric machines has always been an effective tool for scholars to understand the working principles and structure requirements of novel machine topologies. This paper provides an analytical modeling method—the harmonic modeling method (HMM)—for two types of consequent-pole magnetic-geared machines, namely the single consequent-pole magnetic-geared machine (SCP-MGM) and the dual consequent-pole magnetic-geared machine (DCP-MGM). By dividing the whole machine domain into different ring-like subdomains and solving the Maxwell equations, the magnetic field distribution and electromagnetic parameters of the two machines can be obtained, respectively. The two machines were applied in the propulsion systems of hybrid electric vehicles (HEVs). The electromagnetic performances of two machines under different operating conditions were also compared. It turns out that the DCP-MGM can reach a larger electromagnetic torque compared to that of the SCP-MGM under the same conditions. Finally, the predicted results were verified by the finite element analysis (FEA). A good agreement can be observed between HMM and FEA. Furthermore, HMM can also be applied to the mathematical modeling of other consequent-pole electric machines in further study.

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