EV Range Prediction with Multi-Disciplinary Systems Simulation

Ed Wettlaufer_21717
Ed Wettlaufer_21717
Altair Employee
edited April 15 in Altair HyperWorks

EV Range Prediction with Multi-Disciplinary Systems Simulation

 

Ed Wettlaufer

Technical Manager - Mechatronics

­­Background – AFREECAR – Mobility and Freedom for All the World

Mobility improves quality of life by providing access to people, places, and experiences. It also enables economic advancement by providing access to goods and markets. These are considered self-evident truths here in the developed world, but can mobility also transform quality of life and economic development for the world’s poorest people, such as rural Africans?

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Figure 1 - EV Cart Rendition

Imagine a solar-powered EV service that is operated and maintained by a village entrepreneur. This could address the need for many women to individually walk to collect wood from the forest (or to collect water from a well) and provide time for education or to make goods that generate income. High isolation loads in Africa can permit a low speed, lightweight vehicle to travel daily between adjacent villages. This could facilitate access to fertilizer distribution centers, to markets for crops and crafts, and to healthcare that may not exist in the village. The business is funded by users as it enables them to sell their goods. It may also be financed by government education subsidies for women and children. When not providing mobility, it could be the village’s power source for pumping water, grinding grain, and charging cellphones.

Challenges

Much of the EV is built from commercial off the shelf (COTS) parts. Taking the guesswork out of selecting the right parts for the user’s duty cycle is realized by analysis with a systems model. Altair Activate® is the right tool for the task. Altair Activate® software is an open & flexible tool for rapidly modeling and simulating products as multi-disciplinary systems in the form of 1D models (expressed as signal-based or physical block diagrams), optionally coupled to 3D models. The vehicle is decomposed into sub-systems, and each is modeled with physics or test data.

 

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Figure 2 - Activate Systems Model

 

Each sub-system block is reduced to elements representing the components or assemblies thereof, as required. Detail is usually added to elements that contribute to overall response and should be examined as design variables. For example, the terrain varies significantly from pavement to lose soil so rolling resistance contributes significantly to the EV’s range, based on the other “options” selected by the consumer. Options such as battery capacity, photovoltaic wattage and cargo weight play a significant role in the overall range capability, or distance per charge, the EV will achieve.

Photovoltaic test data was collected using Altair Smartworks and used to populate the parameters in photovoltaic model block. A classic “coulomb counter” model was used for the battery block and terrain data gathered from typical rural areas in Ghana, Africa to build the duty cycle and use cases.

Experiments and Results

Ranges were established for design variables and test points identified within each range. The model was exercised through an all-possible-combinations test matrix of the test points and the range of the EV recorded for each test case.

 

Figure 3 - Analysis Test Matrix

The results from this test matrix were used to build a Design of Experiments (DOE) model and conduct a “Fit Study” in Altair’s HyperStudy™ software. HyperStudy™ is a design exploration tool for engineers and designers. It automatically creates intelligent design variants, manages runs, and collects data. Users are then guided to understand data trends, perform trade-off studies, and optimize design performance and reliability.

HyperStudy™ gives insight to the EV options by providing items such as: main effects, interactions, and Pareto plots.

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Figure 4 – Some Study Plots

A Least Squares Method, Fit Study was executed, and a cubic fit model used to generate a regression equation which can be used to estimate the model’s performance based on user input values for the four design variables. This provides the opportunity for the consumer to leverage the computing power of Activate® and HyperStudy™ to make educated decisions for the options they should purchase for their custom EV. This regression equation was used in a script created in Altair Compose®. Compose® software is an environment for doing calculations, manipulating, and visualizing data (including from CAE simulations or test results), programming and debugging scripts useful for repeated computations and process automation.

The user simply inputs the values for the design variables, battery capacity, photovoltaic, weight and rolling resistance, and the script calculates the EV range for any combination.

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Figure 5 - Cart Calculator Compose Script

 

This customer tool is made accessible on AltairOne. AltairOne democratizes simulation by allowing users of Altair units licensing model the on-demand flexibility to access the Altair HW platform and the entire Altair suite of products on-premises or in the cloud. AltairOne delivers instant-on cloud access, lowering the barrier of entry for organizations with limited IT and compute resources to drive their design process with simulation. For those with a higher simulation maturity-level, AltairOne together with Altair units licensing allows organizations to easily and cost-effectively scale resources to meet increased simulation demand.

 

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Figure 6 - Altair365

Conclusion     

Altair products enable the design engineer to model complex 1D systems, study their performance and share the power of simulation with consumers. These tools allow the customer or end user of the EV to objectively compare the cost and performance benefit of the option decisions they make before they buy.