Solar Racing

Type of Resource: Link

Reviews

No reviews

Be the first to write a review

Description

In this 'Energy Education for the 21st Century' design challenge, students construct and evaluate a solar-powered model car. Students utilize the design process and undergo review by their peers to select an optimal gear ratio and components for their car. As a culminating activity, students compete in a Solar Sprint race modeled after the National Renewable Energy Laboratory's Junior Solar Sprint competition.

HS-PS3-3 Design, build, and refine a device that works within given constraints to convert one form of energy into another form of energy.

HS-ETS1-2 Design a solution to a complex real-world problem by breaking it down into smaller, more manageable problems that can be solved through engineering.

Distinguish between causal and correlational relationships in data.

Analyze data to define an optimal operational range for a proposed object, tool, process or system that best meets criteria for success.

Analyze data to identify design features or characteristics of the components of a proposed process or system to optimize it relative to criteria for success.

Ask questions to determine relationships between independent and dependent variables and relationships in models.

Ask questions to determine relationships, including quantitative relationships, between independent and dependent variables.

Construct an explanation that includes qualitative or quantitative relationships between variables that predict(s) and/or describe(s) phenomena.

Undertake a design project, engaging in the design cycle, to construct and/or implement a solution that meets specific design criteria and constraints.

Optimize performance of a design by prioritizing criteria, making tradeoffs, testing, revising, and re-testing.

Apply scientific ideas, principles, and/or evidence to provide an explanation of phenomena and solve design problems, taking into account possible unanticipated effects.

Evaluate competing design solutions based on jointly developed and agreed-upon design criteria.

Evaluate competing design solutions to a real-world problem based on scientific ideas and principles, empirical evidence, and logical arguments regarding relevant factors (e.g. economic, societal, environmental, ethical considerations).

Apply mathematical concepts and/or processes (such as ratio, rate, percent, basic operations, and simple algebra) to scientific and engineering questions and problems.

Apply techniques of algebra and functions to represent and solve scientific and engineering problems.

Apply ratios, rates, percentages, and unit conversions in the context of complicated measurement problems involving quantities with derived or compound units (such as mg/mL, kg/m3, acre-feet, etc.).

Develop or modify a model—based on evidence – to match what happens if a variable or component of a system is changed.

Develop and/or revise a model to show the relationships among variables, including those that are not observable but predict observable phenomena.

Develop and/or use a model to generate data to test ideas about phenomena in natural or designed systems, including those representing inputs and outputs, and those at unobservable scales.

Evaluate merits and limitations of two different models of the same proposed tool, process, mechanism, or system in order to select or revise a model that best fits the evidence or design criteria.

Develop, revise, and/or use a model based on evidence to illustrate and/or predict the relationships between systems or between components of a system.

Collect data to produce data to serve as the basis for evidence to answer scientific questions or test design solutions under a range of conditions.

Plan and conduct an investigation or test a design solution in a safe and ethical manner including considerations of environmental, social, and personal impacts.

Energy is a quantitative property of a system that depends on the motion and interactions of matter and radiation within that system. That there is a single quantity called energy is due to the fact that a system’s total energy is conserved, even as, within the system, energy is continually transferred from one object to another and between its various possible forms.

Although energy cannot be destroyed, it can be converted to less useful forms—for example, to thermal energy in the surrounding environment.

Solar cells are human-made devices that likewise capture the sun’s energy and produce electrical energy.

Energy cannot be created or destroyed, but it can be transported from one place to another and transferred between systems.

Changes of energy and matter in a system can be described in terms of energy and matter flows into, out of, and within that system.

Systems can be designed to cause a desired effect.

Cause and effect relationships can be suggested and predicted for complex natural and human designed systems by examining what is known about smaller scale mechanisms within the system.

Energy cannot be created or destroyed—it only moves between one place and another place, between objects and/or fields, or between systems.

Models (e.g., physical, mathematical, computer models) can be used to simulate systems and interactions—including energy, matter, and information flows—within and between systems at different scales.

Cause and effect relationships may be used to predict phenomena in natural or designed systems.

Algebraic thinking is used to examine scientific data and predict the effect of a change in one variable on another (e.g., linear growth vs. exponential growth).

The transfer of energy can be tracked as energy flows through a designed or natural system.

Models can be used to represent systems and their interactions—such as inputs, processes and outputs—and energy and matter flows within systems.

Energy may take different forms (e.g. energy in fields, thermal energy, energy of motion).

Patterns can be used to identify cause-and-effect relationships.

Small changes in one part of a system might cause large changes in another part.

Patterns of performance of designed systems can be analyzed and interpreted to reengineer and improve the system.

Scientific relationships can be represented through the use of algebraic expressions and equations.

Models are limited in that they only represent certain aspects of the system under study.

Systems can be designed to do specific tasks.

Solar Racing

Reviews

Description

Performance Expectations

Science and Engineering Practices

Disciplinary Core Ideas

Crosscutting Concepts