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As the demand for electric motors and drives grows, designers and manufacturers are faced with the challenge of understanding the effects of often non-deterministic duty cycles on their products. Too often, flaws in the design that can lead to failure only come to light when a prototype is built, or worse, after the product has been launched, leading to delays in product releases or costly recalls. To help mitigate these risks, designers are increasingly turning to simulation technologies that not only allow the engineer to implement the electric drives and motors but also all the various engineering factors, such as mechanical loads, vibrations and thermal effects, together in a single “virtual prototype” to get a clearer idea of how the whole system will behave over multiple duty cycles.

Due to rising fuel prices and environmental concerns, Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEVs) have been gaining market share as fuel-efficient, environmentally friendly alternatives. Lithium-ion batteries are commonly used in EV and HEV applications because of their high power and energy densities. During controls development of HEVs and EVs, hardware-in-the-loop simulations involving real-time battery models are commonly used to simulate a battery response in place of a real battery. One physics-based model which solves in real-time is the reduced-order battery model developed by Dao et al. [1], which is based on the isothermal model by Newman [2] incorporating concentrated solution theory and porous electrode theory [3]. The battery models must be accurate for effective control; however, if the battery parameters are unknown or change due to degradation, a method for estimating the battery parameters to update the model is required.

The analysis of nickel metal hydride (Ni-MH) battery performance is very important for automotive researchers and manufacturers. The performance of a battery can be described as a direct consequence of various chemical and physical phenomena taking place inside the container. In this paper, a physics-based model of a Ni-MH battery will be presented. To analyze its performance, the efficiency of the battery is chosen as the performance measure, which is defined as the ratio of the energy output from the battery and the energy input to the battery while charging. Parametric sensitivity analysis will be used to generate sensitivity information for the state variables of the model. The generated information will be used to showcase how sensitivity information can be used to identify unique model behavior and how it can be used to optimize the capacity of the battery. The results will be validated using a finite difference formulation.

The analysis of nickel metal hydride (Ni-MH) battery performance is very important for automotive researchers and manufacturers. The performance of a battery can be described as a direct consequence of various chemical and physical phenomena taking place inside the container. In this paper, a physics-based model of a Ni-MH battery will be presented. To analyze its performance, the efficiency of the battery is chosen as the performance measure, which is defined as the ratio of the energy output from the battery and the energy input to the battery while charging. Parametric sensitivity analysis will be used to generate sensitivity information for the state variables of the model. The generated information will be used to showcase how sensitivity information can be used to identify unique model behavior and how it can be used to optimize the capacity of the battery. The results will be validated using a finite difference formulation.

Because of its widespread use in almost all the current electric and hybrid electric vehicles on the market, nickel metal hydride (Ni-MH) battery performance is very important for automotive researchers and manufacturers. The performance of a battery can be described as a direct consequence of various chemical and physical phenomena taking place inside the container. To help understand these complex phenomena, a mathematical model of a Ni-MH battery will be presented in this paper. A parametric importance analysis is performed on this model to assess the contribution of individual model parameters to the battery performance. In this paper the efficiency of the battery is chosen as the performance measure. Efficiency is defined by the ratio of the energy output from the battery and the energy input to the battery while charging. By evaluating the sensitivity of the efficiency with respect to various model parameters, the order of importance of those parameters is obtained.