Automotive electronic control systems are expected to respond to input demands in real-time (circa: milliseconds) to ensure occupant and road user safety and comfort. System complexity and real-time computing requirements create significant challenges in proving the robustness of control systems; here robustness is the degree to which a system can function correctly in the presence of unexpected inputs. Evidence shows that faults still escape to customers incurring large warranty costs. Existing test methods can be ineffective in testing robustness with the primary focus being on requirements validation. Evidence from other industries such as IT and medical suggests faults that are difficult to find, manifest due to complex interactions and sequences of events. Research in model based software design, test optimization and formal methods - mathematical based approaches to prove robustness, is abundant in literature. However, modelling and simulation has scalability challenges being computationally intensive, requiring prohibitively excessive time to implement. Model based approaches also need to abstract the concept of “time” making them unsuitable for real-time testing. Yet there is little evidence within the literature pointing to effective sequence interaction testing within real-time test environments. A novel methodology for creating and running t-way input sequence interaction test suites in real-time is presented. For our real-world case study, a safety monitoring system deployed in a prototype embedded electric machine control system is tested with 2688 3-way event sequence interaction tests that trigger a fault in 210 sequences.