Hardware-in-the-loop (HIL) and fault injection testing are widely used in automotive industry to validate hardware and software architectures as best practice and in fulfillment with international functional safety standards. Time and economical investments can constitute an obstacle to the development of effective testing systems, especially for small and medium automotive industries. This paper presents a solution we developed to balance cost with model capabilities and simulation efficiency. The adoption of a model-based approach and the use of a mix of real and emulated sensors and actuators allowed to meet cost and temporal constraints. The presented solution has been developed in six months and is currently adopted to validate new engine control strategies, reducing the testing effort up to 90% compared to manual tests.
Development of an automated test system for ECU software validation: an industrial experience / Bagalini, Enea; Violante, Massimo. - (2016), pp. 103-106. (Intervento presentato al convegno Biennial Baltic Electronics Conference (BEC 2016) tenutosi a Tallinn (Estonia) nel 3-5 Oct. 2016) [10.1109/BEC.2016.7743739].
Development of an automated test system for ECU software validation: an industrial experience
BAGALINI, ENEA;VIOLANTE, MASSIMO
2016
Abstract
Hardware-in-the-loop (HIL) and fault injection testing are widely used in automotive industry to validate hardware and software architectures as best practice and in fulfillment with international functional safety standards. Time and economical investments can constitute an obstacle to the development of effective testing systems, especially for small and medium automotive industries. This paper presents a solution we developed to balance cost with model capabilities and simulation efficiency. The adoption of a model-based approach and the use of a mix of real and emulated sensors and actuators allowed to meet cost and temporal constraints. The presented solution has been developed in six months and is currently adopted to validate new engine control strategies, reducing the testing effort up to 90% compared to manual tests.Pubblicazioni consigliate
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https://hdl.handle.net/11583/2650340
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