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Zhuang, Wei

doi:10.1023/a:1008856607190

Cited by 28 publications

(3 citation statements)

References 8 publications

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“…This enables the algorithm to update its parameters while maintaining constant memory requirements. On the other hand, the LMS algorithm necessitates the retainment of a record of input samples for every tap in the filter, leading to increased memory demands [39,40].…”

Section: Formulation Of the Rls Algorithmmentioning

confidence: 99%

Insulation Detection of Electric Vehicles by Using FPGA-Based Recursive-Least-Squares Algorithm

Bukya,

Malthesh,

Kumar

et al. 2024

WEVJ

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The principal reason for why electric vehicles are required to serve as an alternative to the more widespread gasoline and petroleum-based vehicles used in modern times is due to the use of an environmentally conscious means of transportation or to circumvent the tumultuous economic dealings of the compressed natural gas and petroleum industries. There is a growing daily need for large, high-voltage e-mobilities, mostly driven by anticipated advancements in electric vehicle technology. Consequently, all of the various components of these vehicles must be able to be accommodated within a limited and compact space. The battery is an essential component in e-mobility. The insulation, health monitoring, and problem diagnostics of lithium-ion (Li-ion) batteries are of utmost importance in ensuring these vehicles’ safety and efficient functioning. Real-time and fast insulation detection techniques are required to ensure safety in high-voltage (HV) vehicles and to avoid insulation failure. This paper used the Recursive-Least-Squares (RLS) algorithm because it is computationally efficient for building the insulation detection system. Based on the RLS technique, we proposed field programmable gate array (FPGA)-based algorithms and implemented them using VHDL coding. The FPGA is very fast at detection, and the error is lower. We validated the FPGA results with MATLAB simulation results from the existing literature, and the errors are much less when using FPGAs. An experimental hardware platform was also created to validate the proposed FPGA technique with various motor and resistive loadings on electric vehicles (EVs).

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Section: Formulation Of the Rls Algorithmmentioning

confidence: 99%

Insulation Detection of Electric Vehicles by Using FPGA-Based Recursive-Least-Squares Algorithm

Bukya,

Malthesh,

Kumar

et al. 2024

WEVJ

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“…For the VFF-RLS algorithm, the parameter E(n) is an initial error that is computed at time 'm−1' [12,42]. The subsequent error is given below:…”

Section: Formulation Of the Vff-rls-based Algorithmmentioning

confidence: 99%

FPGA-Based VFF-RLS Algorithm for Battery Insulation Detection in Electric Vehicles

Bukya,

Padma,

Kumar

et al. 2024

WEVJ

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As the adoption of electric vehicles (EVs) continues to rise, attention has switched to ensuring the safety of EV operations. The exponential growth in battery technology over the past several years has changed the face of energy storage and sparked a revolution in several industries. The degradation of battery insulation during regular use is a significant concern. The high voltage (HV) and current levels in HV electric vehicles pose a significant electrical threat.The advancement of electric vehicle technology has led to an increasing presence of HV electric equipment throughout the vehicle. The insulation strength and early health status detection of the batteries are essential in ensuring safety in EVs. This paper studies the different insulation detection techniques and the development of adaptive filter (AF) algorithms based on field-programmable gate arrays (FPGAs) for insulation detection. FPGAs are amongst the most accurate and fast detection techniques among all the insulation detection techniques used so far in electric vehicles. This study proposes an FPGA-based VFF-RLS algorithm for effectively implementing insulation detection in EVs. The experimental test results using FPGAs demonstrate that the proposed method can rapidly monitor changes in insulation resistance (IR). The VFFRLS-based FPGA technique works sufficiently well to reduce errors when dealing with variations in voltage and resistance conditions at the battery terminals.

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“…The block diagram for processing of a finger is shown in Figure3. Each finger consists of downconversion, LPF (Low Pass Filter), despreading, PLL (phase locked loop), and RLS DFE (recursive least square decision feedback equalizer) [13–16] and is responsible for collecting the energy of symbol. Doppler frequency estimations have been set up in each path [17–19].…”

Section: Conventional Rake Receiver Techniquementioning

confidence: 99%

Alternative Approach for Combination of Fingers in Underwater Acoustic Communication

Son

Jeon

Kim

et al. 2016

International Journal of Distributed Sensor Networks

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An underwater acoustic communication channel is time varying and has multipath propagation with bottom and surface reflection. A rake receiver has time diversity effects in multipath propagation environments. We have to recognize the correct path for a rake receiver, as this affects communication performance in the underwater acoustic channel. In this paper, we propose a more reliable rake receiver based on BER (bit error rate) of training sequence duration. We conducted simulations and lake trials to evaluate the performance of the proposed method. When the channel coding technique was not applied, the uncoded BER performances of the proposed method, the conventional method, and the nonrake method in the lake trial were 0.016, 0.088, and 0.141, respectively.

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Untitled

Cited by 28 publications

References 8 publications

Insulation Detection of Electric Vehicles by Using FPGA-Based Recursive-Least-Squares Algorithm

Insulation Detection of Electric Vehicles by Using FPGA-Based Recursive-Least-Squares Algorithm

FPGA-Based VFF-RLS Algorithm for Battery Insulation Detection in Electric Vehicles

Alternative Approach for Combination of Fingers in Underwater Acoustic Communication

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