An Exergoeconomic Analysis of Hybrid Electric Vehicle Thermal Management Systems

2013 ◽  
Vol 6 (2) ◽  
Author(s):  
H. S. Hamut ◽  
I. Dincer ◽  
G. F. Naterer
Keyword(s):  
Electric Vehicle ◽  
Thermal Management ◽  
Hybrid Electric Vehicle ◽  
System Component ◽  
Exergy Destruction ◽  
Thermal Management System ◽  
Investment Cost ◽  
Hybrid Electric ◽  
Exergoeconomic Analysis ◽  
The Cost

In this paper, exergy analysis of a hybrid electric vehicle thermal management system (TMS) is initially investigated in order to find the areas of inefficiencies and exergy destruction within each system component. In the analysis, advanced exergy modeling is utilized to study both endogenous/exogenous and avoidable/unavoidable exergy destructions for each component of the system and further understand the interactions among the TMS components and determine the underlying reasons behind the exergy destructions. Moreover, this approach is also used to enhance exergoeconomic analyses by calculating the endogenous/exogenous and avoidable/unavoidable portion of the investment and exergy destruction costs (so-called advanced exergoeconomic analysis) in order to improve the cost effectiveness of the system and provide information on how much of the cost can be avoided for each component. Based on the analysis, it is determined that exogenous exergy destruction is small but significant portion of the total exergy destruction in each component (up to 40%, in the chiller and thermal expansion valves) and that large portion of the exergy destruction within the components (up to 70%, in the compressor) could be potentially avoided. Moreover, it is determined that electric battery, compressor, and chiller are dominated by investment cost, whereas the condenser and evaporator are dominated by the cost of exergy destruction in the system.

Study of Thermal Management System for a Series-Parallel Hybrid Electric Vehicle Using Numerical Simulation

2013 ◽  
Vol 300-301 ◽  
pp. 932-937 ◽  
Author(s):  
Xiao Xia Sun ◽  
Yi Chun Wang ◽  
Chun Ming Shao ◽  
Yu Feng Wu ◽  
Guo Zhu Wang
Keyword(s):  
Electric Vehicle ◽  
Thermal Management ◽  
Management System ◽  
Hybrid Electric Vehicle ◽  
Heat Dissipation ◽  
Pollutant Emission ◽  
Parallel Hybrid Electric Vehicle ◽  
Thermal Management System ◽  
Parallel Hybrid ◽  
Hybrid Electric

Advanced thermal management system (TMS) has the potential to increase the life of the vehicle’s propulsion, and meanwhile, decrease fuel consumption and pollutant emission. In this paper, an advanced TMS which is suitable for a series-parallel hybrid electric vehicle (SPHEV) is presented. Then a numerical TMS model which can predict the thermal responses of all TMS components and the temperatures of the engine and electric components is developed. By using this model, the thermal response of the TMS over a realistic driving cycle is simulated. The simulation result shows that the TMS can fulfill the heat dissipation requirement of the whole vehicle under different driving conditions. It also demonstrates that a numerical model of TMS for SPHEV is an effective tool to assess design concepts and architectures of the vehicle system during the early stage of system development.

Experimental and Theoretical Efficiency Investigation of Hybrid Electric Vehicle Battery Thermal Management Systems

2014 ◽  
Vol 136 (1) ◽  
Author(s):  
H. S. Hamut ◽  
I. Dincer ◽  
G. F. Naterer
Keyword(s):  
Electric Vehicle ◽  
Thermal Management ◽  
Hybrid Electric Vehicle ◽  
Operating Conditions ◽  
Battery Thermal Management ◽  
Thermal Management System ◽  
Battery Thermal Management System ◽  
Electric Vehicle Battery ◽  
Hybrid Electric ◽  
Reported Data

In this study, a thermodynamic model of a hybrid electric vehicle battery thermal management system (TMS) is developed and the efficiency of the system is determined based on different parameters and operating conditions. Subsequently, a TMS test bench is used with a production vehicle (Chevrolet Volt) that is fully instrumented in order to develop a vehicle level demonstration of the study. The experimental data are acquired under various conditions using an IPETRONIK data acquisition system, along with other reported data in the literature, to validate the numerical model results. Based on the analyses, the condenser and evaporator pressure drop, compressor work and compression ratio, evaporator heat load and efficiency of the system are determined both numerically and experimentally. The predicted results are determined to be within 6% of the conducted experimental results and within 15% of the reported results in the literature.

Hybrid Electric Vehicle Energy Management With Battery Thermal Considerations Using Multi-Rate Dynamic Programming

2013 ◽  
Author(s):  
Rajit Johri ◽  
Wei Liang ◽  
Ryan McGee
Keyword(s):  
Dynamic Programming ◽  
Electric Vehicle ◽  
Thermal Management ◽  
Hybrid Electric Vehicle ◽  
Computational Time ◽  
Bulk Temperature ◽  
Thermal Dynamics ◽  
Battery Thermal Management ◽  
Battery Capacity ◽  
Hybrid Electric

Battery capacity and battery thermal management control have a significant impact on the Hybrid Electric Vehicle (HEV) fuel economy. Additionally, battery temperature has a key influence on the battery health in an HEV. In the past, battery temperature and cooling capacity has not been included while performing optimization studies for power management or optimal battery sizing. This paper presents an application of Dynamic Programming (DP) to HEV optimization with battery thermal constraints. The optimization problem is formulated with 3 state variables, namely, the battery State Of Charge (SOC), the engine speed and the battery bulk temperature. This optimization is critical for determining appropriate battery size and battery thermal management design. The proposed problem has a major challenge in computation time due to the large state space. The paper describes a novel multi-rate DP algorithm to reduce the computational challenges associated with the particular class of large-scale problem where states evolve at very different rates. In HEV applications, the battery thermal dynamics is orders of magnitude slower than powertrain dynamics. The proposed DP algorithm provides a novel way of tackling this problem with multiple time rates for DP with each time rate associated with the fast and slow states separately. Additionally, the paper gives possible numerical techniques to reduce the DP computational time and the time reduction for each technique is shown.

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