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Heavy Duty Vehicle Cooling System Auxiliary Load Management Control: Evaluating the Maximum Gain of Implementing an Advanced Control Strategy
Technical Paper
2014-01-2341
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Vehicle thermal management covers the engineering field of solutions that maintain the complete vehicle in acceptable operating conditions regarding component and fluid temperatures in an engine. The maximum efficiency rating of a Diesel engine reaches up to 45%.
In order to improve the fuel efficiency of the vehicle one can reduce the losses generated by the cooling system. Ideally, the full motive force of the engine should be used for propulsion and new and more efficient energy sources have to be explored to power the secondary systems (cooling, compressed air…).
This paper introduces a dynamic programming algorithm which is used to determine the maximum gains during operation for a given architecture of the cooling system of a Heavy Duty Truck. The algorithm, based in Bellman principle, will determine the best control trajectory for the pump and the fan according to energetic and control goals (fuel economy, regulation of temperature…). For this purpose, a reduced model of the cooling system based on energy balance equations has been determined and validated through simulations.
An optimal control path is determined by the algorithm for a given cycle, which is then used as an input to the controllers in a simulation platform for the same reference driving cycle in order to calculate more accurately the energy consumption. The simulation platform is built in GT-Suite (system model) and Matlab/Simulink (inputs). The result show how it is possible to reduce the energy consumption by optimizing the control strategy of the cooling system, in particular hints are given in terms of thermostatic valve threshold tuning.
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Sermeno, S., Bideaux, E., Morgan, T., and Nguyen, D., "Heavy Duty Vehicle Cooling System Auxiliary Load Management Control: Evaluating the Maximum Gain of Implementing an Advanced Control Strategy," SAE Technical Paper 2014-01-2341, 2014, https://doi.org/10.4271/2014-01-2341.Data Sets - Support Documents
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