The Vehicle Engine Cooling System Simulation Part 1 - Model Development

Arici, O.; Johnson, John H.; Kulkarni, Ajey J.

doi:10.4271/1999-01-0240

Cited by 35 publications

(8 citation statements)

References 13 publications

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“…It is assumed that a fraction, r, of this heat transfers to the coolant water. The value for this fraction varies between engine setups, so to increase the generality of the study results from simulations were examined for different values within the plausible interval r ∈ [0.1, 0.5]; see e.g., [1]. The resulting amount of heat from the engine that transfers to the coolant liquid becomeṡ…”

Section: A) Engine (Converter and Heat Source)mentioning

confidence: 99%

Assessing the potential of prediction in energy management for ancillaries in heavy-duty trucks

Nilsson¹,

Johannesson

Askerdal

2014

2014 European Control Conference (ECC)

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The degree of importance of prediction in the control of ancillary systems for conventional heavy-duty trucks is investigated, with focus on fuel economy. An optimal control law that utilizes prediction is compared with a suboptimal causal control law. The incentive for this investigation is that the suboptimal control law is less complex to develop and implement for the considered system. The results are not general since only a limited amount of ancillary systems have been modeled, only two different drive cycles have been evaluated and simplified mathematical component models for a specific test truck have been used in the optimization problem. Nevertheless, preliminary results from this investigation indicate that simple suboptimal control laws can yield close to the same improvements in fuel efficiency as a predictive controller, when compared to a baseline control law. Tuning complexity is expected to rise when more ancillaries are included in the energy management problem. This can be a valid argument to incorporate prediction in future work.

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Section: A) Engine (Converter and Heat Source)mentioning

confidence: 99%

Assessing the potential of prediction in energy management for ancillaries in heavy-duty trucks

Nilsson¹,

Johannesson

Askerdal

2014

2014 European Control Conference (ECC)

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“…Developing a cooling system model for a complete vehicle is essential for understanding the interaction between the systems and optimizing the cooling package for the vehicle. Arici, Johnson and Kulkarni [2] simulated the thermal response of the cooling system of an on-highway heavy-duty diesel truck under steady and transient conditions using Vehicle Engine Cooling System Simulation (VECSS) computer code developed originally by Ursini [3] and Chang [4] at Michigan Technological University.…”

Section: Introductionmentioning

confidence: 99%

Numerical Simulation of a 2018 F1 Car Cooling System for Silverstone Circuit

Otero¹,

Samuel²

2018

SAE Technical Paper Series

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The thermal management of a Formula 1 car is a challenging task as it involves multiple components, systems and multiple sources of thermal energy. The present work attempts to model a representative F1 car following 2018 F1 regulations directly linked to the cooling systems requirements and performance. The main purpose of this work is to simulate the steady and transient behaviour of the cooling system when the vehicle is in a qualifying lap, and during the entire race, including the wait in the starting grid and the pit stops. This model includes the sub-models representing internal combustion engine, hybrid powertrain, vehicle, driver and an appropriate cooling system composed of radiators, pumps and expansion tanks. This work validates the cooling system of a representative 2018 F1 car for the Silverstone Circuit. This model is capable of simulating the overall thermal performance of the F1 car for sizing the cooling system for most of the F1 circuits. This paper presents a systematic approach followed for modelling a representative F1 car based on 2018 regulations, methods used for deriving appropriate data from various sources, approach used for validating the model and finally the strengths of the validated model for sizing the cooling system.

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“…The dynamic modeling of the heat transfer among the engine components, is undoubtedly of great importance for both the engine's and the CHP's operation simulation [10]. Equation 3.34 is a simple energy balance on the boundaries of the cylinder wall.…”

Section: Energy Balancementioning

confidence: 99%