Vehicle electrification

Electrical and signal processing aspects

Together with feedback from customers and technology partners, Prenscia is developing solutions for improving the process of electric motor efficiency and loss mapping, optimizing power measurement and analysis, and real-world battery usage and vehicle efficiency assessment.

Electric and signal processing aspects of vehicle electrification

Together with feedback from customers and partners, Prenscia is gaining a deeper understanding of the technological requirements needed for calculating accurate power measurements and producing efficiency maps, optimizing power measurement and analysis, and understanding real-world battery usage for vehicle efficiency assessment.


Electric motor efficiency and loss mapping

In order to maximize the range and overall efficiency of an electric vehicle, a properly optimized electric motor controller is required. An 'efficiency contour map' is a powerful tool that describes how efficient the powertrain is. Design optimization is concerned with broadening and maximizing the optimal region.

Calculating an efficiency map involves sweeping the machine through all possible torque and speed settings with respect to the multiple inverter operating modes. The traditional approach involves low-frequency analogue measurement devices - such as multimeters and AC Power Analyzers - along with digital torque sensors. With modern high-speed digital data acquisition systems such as eDrive, it is now possible to perform efficiency analysis directly on the digitized data. This accelerates the test considerably and allows more complex analysis of the transient dynamic power measurements that are associated with real-world driving and the Worldwide Harmonized Light Vehicle Test Procedure (WLTC). Detailed efficiency maps based on this high-speed digital data are produced using nCode GlyphWorks, which can calculate power and energy consumption for all electric motor states. The Surface Plot glyph is ideal for torque vs speed efficiency and loss mapping for AC motor tests as well as other applications for general XYZ mapped data.

Power measurement and analysis

Accurate power measurements are essential for optimizing the motor control and estimating the vehicle range. An electric powertrain comprises of 5 key components - DC battery, inverter/controller, AC motor, gearbox/epicyclic, and whole-vehicle body mass response - that each contribute to the overall energy efficiency of the vehicle.
Unlike the conventional electricity grid, electric vehicles convert DC to AC using an electrical inverter. These produce a frequency-modulated, non-sinusoidal, transient dynamic output signal, which gives rise to harmonic distortion and 'ripple' in the output torque. This in turn is a source of inefficiency and causes noise and structural vibrations through the vehicle structure leading to vibration-induced damage in some cases.
nCode GlyphWorks offers advanced digital signal post-processing tools to analyse the dynamic power over all component systems and operating states. Electrical and mechanical data are combined, and frequency analysis is used to assesses the dynamic responses. The effect of torque-ripple on vibration-induced damage can be determined. Discrete operating states can be combined to understand how vehicle efficiency is influenced by different real-world operating profiles.

Real-world battery usage and vehicle efficiency assessment

The range of an electric vehicle varies significantly based on the road and driving conditions encountered in the real-world. The total energy required to propel a vehicle and the total energy that can be regenerated is based on the quantities of kinetic factors of the whole vehicle under real-world conditions: rolling resistance, aerodynamic drag, gradient resistance, and inertial resistance.

The actual power of the vehicle and its overall holistic efficiency can be calculated using data from the vehicle CAN and GPS. Data obtained from a large fleet of vehicles may be combined in nCode GlyphWorks to identify the various design usage profiles and determine a 95% target customer. By understanding trends in the overall vehicle efficiency over time, better prognostic models can also be calculated to improve the real-world reliability of the vehicle and maintain its State-of-Health (SOH).

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