Sr. Controls Engineer, Active Chassis Systems - Newark, United States - Lucid Motors

Description

We are currently seeking a Controls Engineer motivated by the application of control theory to achieve desired vehicle dynamics.

In this role, you will have the opportunity to design control systems that help elevate vehicle ride and handling attributes via the actuation of motors, brakes and the suspension system.

Our ideal candidate exhibits a can-do attitude and approaches problem solving with vigor and determination.

Candidates will be expected to demonstrate excellence in their respective fields, to possess the ability to learn quickly and to strive for perfection within a fast-paced environment.

The Role:
Application of concepts in control theory to a variety of domains like handling dynamics, ride dynamics and NVH to achieve desired vehicle attributes
Application of linear analysis techniques and frequency domain analysis
Develop simulation tools that enable objective decision making for control system architectures, calibration and formulating requirements
Develop requirements and related test cases for features modeled in Matlab/Simulink
Assist integration of features into the controller code base
Test the developed software on the vehicle and assist in calibration of the features
Occasional travel for vehicle testing


Minimum Qualifications:
4 years of experience with control systems (5+ Bachelor of Science)
Good knowledge of model-based design using Matlab/Simulink/Stateflow
Good understanding of vehicle handling and ride dynamics
Good understanding of state estimation and sensor fusion techniques
Expertise in control theory concepts like classical control theory, modern control theory, MRAC, non-linear control theory, robust control
Working knowledge of chassis hardware such as dampers, springs, anti-roll bars, brakes, steering etc.


Preferred Skills:
Good understanding of C/C++
Experience with Embedded coder in Matlab/Simulink
Experience with tools like JAMA/JIRA/Git/Confluence
Experience in working with cross functional teams
Common understanding of ISO 26262, Autosar, ASPICE
Knowledge of adaptive filtering is advantageous
Experience with CAN analysis tools likeCANoe, CANalyzer, and CANape

Bachelor of Science (Master of Science preferred), in the areas of electrical engineering, mechanical engineering, automotive systems, or other related fields.

Experience with performance driving is a plus


Education Requirements:

Bachelor of Science (Master of Science preferred), in the areas of electrical engineering, mechanical engineering, automotive systems, or other related fields.

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