Sendyne Corporation

Sensata Technologies, Inc.

Nicolas Clauvelin

Victor Marten

Ioannis Milios

Robert C Melville

An isolation monitoring approach according to the invention is defined with respect to first and second battery connection positions, each of which is not tied to a chassis. First and second respective resistor strings, each having a first end and a second end, are each connected at their first end to the respective first and second battery connection positions. The first and second resistor strings are each connected at their second end to the chassis. In each of the first and second resistor strings, an optically-controlled MOSFET relay is connected across part of the resistor string. Connected to each of the resistor strings, at a point between the MOSFET relay and the chassis, is a respective voltage measurement circuit connected to measure voltage relative to the chassis. In operation, the MOSFETs associated with the resistor strings can be turned on and off. This brings about an excitation signal with respect to the resistor strings, and the voltage measurement circuits can measure the voltages during the time of the excitation signal, comparing them with the voltages in the absence of the excitation signal. This permits arriving at an inferred value for isolation loss along a modeled leakage path between the associated battery connection positions and the chassis. In the event of an isolation failure, the event can be annunciated.

Isolation monitoring

Switching of particular inputs in a signal processing channel permits an independent evaluation of that signal processing channel, in a system where there are at least two signal processing channels, one of which is able to be calibrated while the other of which is measuring current in a shunt. Switching a controlled current through a shunt, the controlled current being small in value compared with an overall current being measured, permits yet another independent evaluation of the shunt.

Functional safety of measurements

Wide deployment of high voltage battery systems in traction, industrial and renewable energy installations is raising the concerns for human safety. Exposure to hazardous high voltages may occur due to deterioration of insulation materials or by accidental events. It is thus important to monitor for such faults and being able to provide timely warnings to affected persons. For this purpose it has become mandatory for electrified passenger vehicles (CFR 571.305) to maintain high isolation values which can be continuously monitored by electrical isolation monitoring devices. The task of monitoring isolation resistance within the electrically noisy car environment is not a trivial task and the solution to this problem has become quickly a field of research and innovation for all affected industries.

Isolation monitoring device and method

The inventive disclosures described herein pertain to an improved physical analog computer that features the ability to evaluate arbitrary non-linear functions using an interpolation method based on Chebyshev polynomials. What has been developed is an improved method for non-linear-function generation in hybrid computing that relies on Chebyshev interpolation. The method requires an initial computation of the interpolation coefficients, which is to be carried out in the digital domain. These coefficients, along with the domain of definition of the non-linear function to be generated, are used during the programming of the analog domain to set multiplier and summer elements.

Analog computing implementing arbitrary non-linear functions using Chebyshev-polynomial-interpolation schemes and methods of use

A complete model numerical solver resides on an embedded processor for real time control of a system. The solver eliminates the need for custom embedded code, requiring only model equations, definition of the independent and dependent variables, parameters and input sources information as input to solve the model equations directly. Through elimination of the need for custom code, the solver speeds up the model deployment process and provides the control application sophisticated features such as Automatic Differentiation, sensitivity analysis, sparse linear algebra techniques and adaptive step size in solving the model concurrently.

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New York, NY, United States of America

Nicolas Clauvelin