Browse Topic: On-board vehicle charging systems
Lithium-ion cells operate under a narrow range of voltage, current, and temperature limits, which requires a battery management system (BMS) to sense, control, and balance the battery pack. The state of power (SOP) estimation is a fundamental algorithm of the BMS. It operates as a dynamic safety limit, preventing rapid ageing and optimizing power delivery. SOP estimation relies on predictive algorithms to determine charge and discharge power limits sustainable within a specified time frame, ensuring the cell design constraints are not violated. This paper explores various approaches for real-time deployment of SOP estimation algorithms for a high-power lithium-ion battery (LIB) with a low-cost microcontroller. The algorithms are based on a root-finding approach and a first-order equivalent circuit model (ECM) of the battery. This paper assesses the practical application of the algorithm with a focus on processor execution time, flash memory and RAM allocation using a processor-in-the
Good driving practices, encompassing actions like maintaining smooth acceleration, sustaining a consistent speed, and avoiding aggressive maneuvers, can yield several benefits. These practices enhance energy efficiency, reduce accident risks, and significantly lower maintenance costs. Consequently, the presence of a system capable of providing actionable insights to promote such driving behavior is crucial. Addressing this need, the Drive-GPT model is introduced, representing an AI-based generative pre-trained transformer. Within this study, the transformative potential of deep learning networks, specifically based on transformers, is showcased in capturing the typical driving patterns exhibited by individuals in diverse road, traffic, weather, and vehicle health scenarios. The model's training dataset comprises an extensive 90 million data points from multivariate time series originating from telematics systems in 100 vehicles traversing eight distinct Indian cities over a six-month
This paper aims at analysing the effect of regeneration braking on the amount of energy harnessed during vehicle braking, coasting and its effect on the drive train components like gear, crown wheel pinion, spider gear & bearing etc. Regenerative braking systems (RBS) is an effective method of recovering the kinetic energy of the vehicle during braking condition and using this to recharge the batteries. In Battery Electric Vehicles (BEV), this harnessed energy is used for controlled charging of the high voltage batteries which will help in increasing the vehicle range eventually. Depending on the type of the powertrain architecture, components between motor output to the wheels will vary, i.e., in an e-axle, motor is coupled with a gear box which will be connected with differential and the wheels. Whereas in case of a central drive architecture, motor is coupled with gearbox which is connected with a propeller shaft and then the differential and to the wheels. All the components
In recent years, global warming, depletion of fossil fuels, and reducing pollution have become increasingly prominent issues, resulting in demand for environmentally-friendly two-wheeled vehicles capable of reducing CO2 emissions. However, it remains necessary to meet customers’ expectations by providing smaller drivetrains, lighter vehicles, and support for long-distance riding, among other characteristics. In the face of this situation, hybrid electric vehicle (HEV) systems are considered to be the most realistic method for creating environmentally-friendly powertrains and are widely used. This research introduces a hybrid electric two-wheeled vehicle fitted with an electrical variable transmission (EVT) system, a completely new type of electrical transmission that meets the aforementioned needs, achieving enhanced fuel efficiency with a compact drivetrain. The EVT system comprises double rotors installed inside the stator. The hybrid electric two-wheeled vehicle equipped with the
This SAE Information Report provides test methods and determination options for evaluating the maximum wheel power and rated system power of vehicles with electrified vehicle powertrains. The scope of this document encompasses passenger car and light- and medium-duty (GVW <10000 pounds) hybrid-electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), battery electric vehicles (BEVs), and fuel-cell electric vehicles (FCEVs). These testing methods can also be applied to conventional ICE vehicles, especially when measuring and comparing wheel power among a range of vehicle types. This document version includes a definition and determination methodology for a rated system power that is comparable to traditional internal combustion engine power ratings (e.g., SAE J1349 and UN ECE R85). The general public is most accustomed to “engine power” and/or “motor power” as the rating metric for conventional and electrified vehicles, respectively. Wheel power will always be a lower-power
To reduce the energy consumption level of electric vehicles, the working range of the regenerative braking system will gradually expand to the high state of charge of the battery. The time delay in the control signal transmission path of the high state of charge regenerative braking control process will affect the regenerative braking. At the same time, regenerative braking under a high state of charge puts forward higher requirements for the control accuracy of regenerative current. In the research of this paper, the motor model, battery model, and vehicle dynamics model are firstly established by using MATLAB/Simulink, and the dynamic relationship between regenerative current and regenerative braking torque is analyzed at the same time. Considering the system time delay, this paper proposes a high-charge regenerative braking control strategy (SPPC) that combines Smith prediction and prescribed performance control. This control strategy can not only compensate for the system time
Regenerative braking without question greatly impacts brake pad service life in the field, in most cases extending it significantly. Estimating its impact precisely has not been an overriding concern - yet - due in part to the extensive sharing of brake components between regen-intensive battery-electric and hybrid vehicles, and their more friction-brake intensive internal combustion engine powered sibling. However, a multitude of factors are elevating the need for a more accurate estimation, including the emerging of dedicated electric vehicle architectures with opportunities for optimizing the friction brake design, a sharp focus on brake particulate emissions and the role of regenerative braking, a need to make design decisions for features such as corrosion protection for brake pad and pad slide components, and the emergence of driver-facing features such as Brake Pad Life Monitoring. Tackling this question raises questions such as “is the proven braking energy and temperature
Reducing exhaust emissions has been a major focus of research for a number of years since internal combustion engines (ICE) contribute to a large number of harmful particles entering the environment. As a way of reducing emissions and helping to tackle climate change, many countries are announcing that they will ban the sale of new ICE vehicles soon. Electrical vehicles (EVs) represent a popular alternative vehicle propulsion system. However, although they produce zero exhaust emissions, there is still concern regarding non-exhaust emission, such as brake dust, which can potentially cause harm to human health and the environment. Despite EVs primarily using regenerative braking, they still require friction brakes as a backup as and when required. Moreover, most EVs continue to use the traditional grey cast iron (GCI) brake rotor, which is heavy and prone to corrosion, potentially exacerbating brake wear emissions. This study concentrates on emissions from a conventional grey cast iron
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