Based on this, this paper uses the visualization method to preprocess, clean, and parse collected original battery data (hexadecimal), followed by visualization and analysis
AI Customer ServiceStrong correlations were observed between range and battery capacity, top speed, curb weight, and acceleration (with Pearson coefficients of 0.90, 0.79, 0.70, and −0.84, respectively). Regression analysis is a simple
AI Customer ServiceAccording to the traffic conditions and ambient temperature, the actual operation data of 19 battery electric buses in one year are divided into 12 control groups and the
AI Customer ServiceComparison of battery technologies for new energy vehicles. Traditional cars will upgrade to light weight, energy saving . regression analysis.
AI Customer ServicePrincipal component analysis, Bayes regularization BP neural network, sensitivity analysis and multilayer linear regression are used to analyze data from 476 valid questionnaires, the results
AI Customer ServiceState of charge (SOC) and state of energy (SOE) are the key factors that reflect the safe and range driving of new energy vehicles. This paper proposes an optimized
AI Customer ServiceFor this purpose, regression models that consider both EV dynamic behaviour and powertrain efficiency, have been developed. 14-16 For example, the model developed in
AI Customer ServiceRegression analysis is used for mathematical formulations while Deep Sleep Heuristic algorithms in MATLAB environment is used for the optimization process for BESS
AI Customer ServiceA detailed dataset of the technical specifications of commercial EV models manufactured from 2008 to 2021 was collected through web mining. Strong correlations were observed between range and battery capacity, top
AI Customer ServiceAs of June 2019, the number of new energy vehicles in China has reached about 3.44 million, and the number of pure electric vehicles has reached 2.81 million,
AI Customer ServiceIn order to alleviate the pressures of environmental pollution and the energy crisis, and to lay out and capture huge emerging markets as soon as possible, all countries in
AI Customer Servicebattery management system operation for optimal utilization of a battery pack in various operating conditions. This article proposes an approach to estimate battery capacity
AI Customer ServiceThe primary objective of this work is to develop a more versatile machine learning model (i.e., support vector regression [SVR]) capable of estimating battery capacity under fast
AI Customer Servicebattery management system operation for optimal utilization of a battery pack in various operating conditions. This article proposes an approach to estimate battery capacity based on two...
AI Customer Serviceenergy consumption estimation or energy consumption prediction over a trip for eco-route planning.13 The existing regenerative braking models are improved in this study by
AI Customer ServiceAssessing and predicting the SOH of lithium batteries can help us understand the changes in battery performance, timely detect potential faults, take measures to extend the
AI Customer ServiceIn this paper, the energy consumption of battery (EC b), motor (EC m), and auxiliaries (EC a) as well as the energy restored to battery during braking energy regeneration
AI Customer ServiceThe battery is one of the primary energy sources for a green and clean mode of transportation, but variations in driving profiles (NYCC, Artemis Urban, WLTP class-1) and
AI Customer ServiceState of charge (SOC) and state of energy (SOE) are the key factors that
AI Customer ServiceA detailed dataset of the technical specifications of commercial EV models manufactured from 2008 to 2021 was collected through web mining. Strong correlations were
AI Customer ServiceIn this paper, the energy consumption of battery (EC b), motor (EC m), and
AI Customer ServiceAnalysis and V isualization of New Energy V ehicle Battery Data Wenbo Ren 1,2,†, Xinran Bian 2,3,†, Jiayuan Gong 1,2, *, Anqing Chen 1,2, Ming Li 1,2, Zhuofei Xia 1,2 and Jingnan Wang 1,2
AI Customer ServiceAccording to the traffic conditions and ambient temperature, the actual operation data of 19 battery electric buses in one year are divided into 12 control groups and the reference energy
AI Customer ServiceBased on this, this paper uses the visualization method to preprocess, clean, and parse collected original battery data (hexadecimal), followed by visualization and analysis of the parsed data
AI Customer ServiceRegression analysis is used for mathematical formulations while Deep Sleep
AI Customer ServiceBased on the ridge regression model, Ref. used the new energy vehicle operation data provided by the Shanghai New Energy Vehicle Public Data Collection and Monitoring
AI Customer ServiceIt should be noted that while the proposed linear regression equation yields a higher error rate than estimating the EV range using a power consumption model in the literature (8.6% vs. approximately 1%), it requires significantly fewer parameters.
Nonetheless, an accurate power-based EV energy consumption model is crucial to obtain a precise range estimation. This paper describes a study on EV energy consumption modelling. For this purpose, EV modelling is carried out using MATLAB/Simulink software based on a real EV in the market, the BMW i3.
However, this approach is not accurate since it does not consider the changes in driving conditions that may occur. 10 EV energy consumption estimation models can be classified in three main categories: Analytical, Statistical and Computational models. 7
The consumed energy, Econs, is calculated as per unit of distance (Wh/m) derived from the battery power output Pbat 29: Pb − out and Pb − in are respectively the power provided by the battery for vehicle motion and the power regenerated to charge the battery considering electric motor braking capabilities in generator mode.
For EV range estimation, an accurate estimation of the EV's energy consumption is vital and is therefore the purpose of this study. In this study, the energy flow is only considered inside the vehicle so, the energy flow between the grid and vehicle is out of the framework. Generally, the EV energy consumption refers to the sum of:
The model consists of an internal voltage source (VOC), an ohmic resistance (RO) and polarisation resistance (R1) and capacitance (C1). The model parameters VOC, RO, R1 and C1 are defined as a function of the battery SoC.
We are deeply committed to excellence in all our endeavors.
Since we maintain control over our products, our customers can be assured of nothing but the best quality at all times.