Modeling and Optimization of Heat Dissipation Structure of EV Battery Pack

In order to solve the problems of high temperature and inconsistency in the operation of electric vehicle（ EV） battery pack,computational fluid dynamics（ CFD） simulation method is used to simulate and optimize the heat dissipation of battery pack. The heat generation rate at different discharge magnifications is identified by establishing the heat generation model of the battery. In the forced air cooling mode,the Fluent software is used to compare the effects of different inlet and outlet directions,inlet angles,outlet angles,outlet sizes and inlet air speeds on heat dissipation. The simulation results show that the heat dissipation effect of the structure with the inlet and outlet on the same side is better than that on the different sides; the appropriate inlet angle and outlet width can improve the uniformity of temperature field; the increase of the inlet speed can improve the heat dissipation effect significantly. Compared with the steady temperature field of the initial structure,the average temperature after structure optimization is reduced by 4. 8℃ and the temperature difference is reduced by 15. 8℃,so that the battery can work under reasonable temperature and temperature difference.

Thermal heat flux distribution prediction in an electrical vehicle battery cell using finite element analysis and neural network

In terms of battery design and evaluation,Electric Vehicles(EVs)are receiving a great deal of attention as a modern,eco-friendly,sustainable transportation method.In this paper,a novel battery pack is designed to maintain a uniform temperature distribution,allowing the battery to operate within its optimal temperature range.The proposed battery design is part of a main channel where a portion of cool air will pass from an inlet then exit from an outlet where a uniform temperature distribution is maintained.First,a 3-D model of a battery cell was created,followed by thermal simulation for 15C,25C,and 35C ambient temperatures.The simulation results reveal that the temperature distribution is nearly uniform,with slightly higher values in the middle portion of the cell height.Second,using finite element analysis(FEA),it was determined that the heat flux per unit area is nearly uniform with a slight increase at the edges.Third,a machine learning model is proposed by utilizing a neural network(NN).Lastly,the heat flux values were predicted using the NN model that was proposed.The model was assessed based on statistical measures where a root mean square error(RMSE)value of 0.87%was achieved.The NN outperformed FEA in terms of time consumption with a high prediction accuracy,leveraging the potential of adopting machine learning over FEA in related operational assessments.

Energy cost minimization through optimization of EV, home and workplace battery storage

Besides grid-to-vehicle(G2 V) and vehicle-to-grid(V2 G) functions, the battery of an electric vehicle(EV) also has the specific feature of mobility. This means that EVs not only have the potential to utilize the storage of cheap electricity for use in high energy price periods, but can also transfer energy from one place to another place. Based on these special features of an EV battery, a new EV energy scheduling method has been developed and is described in this article. The approach is aimed at optimizing the utilization EV energy for EVs that are regularly used in multiple places. The objective is to minimize electricity costs from multiple meter points. This work applies real data in order to analyze the effectiveness of the method. The results show that by applying the control strategy presented in this paper at locations where the EVs are parked, the electricity cost can be reduced without shifting the demand and lowering customer's satisfaction. The effects of PV size and number of EVs on our model are also analyzed in this paper. This model has the potential to be used by energy system designers as a new perspective to determine optimal sizes of generators or storage devices in energy systems.

Analysis and Comparison of Two Wireless Battery Charger Arrangements for Electric Vehicles

The paper deals with wireless battery chargers(WBCs)for plug-in electric vehicles(PEVs)and analyzes two arrangements for the receiver of a series-series resonant WBC.The first arrangement charges the PEV battery in a straightforward manner through a diode rectifier.The second arrangement charges the PEV battery through the cascade of a diode rectifier and a chopper whose input voltage is kept constant.Figures of merit of WBCs such as efficiency and sizing factor of both the power source and the transmitter/receiver coils are determined.Afterwards,they are discussed and compared with reference to the case study of WBC for an electric city car.A proposal to optimize the efficiency of the second arrangement by a suitable selection of the chopper input voltage is presented.Measurements on the efficiency of the two arrangements are included to support the theoretical results.