Cyclical TRIZ for brushless direct current motor evolution: From short-term adjustments to long-term transformation

Abstract

As engineering systems accumulate increasing layers of functional, structural, and behavioral complexity, the ability to guide their evolution with coherent, theory-driven frameworks has become essential. This paper presents a cyclical theory of inventive problem solving (TRIZ)-based roadmap for the evolution of brushless direct current (BLDC) motors, guiding development from short-term corrective actions to long-term transformative strategies. The approach structures action into three coupled cycles that respectively prioritize rapid technical remedies, system-level contradiction resolution, and strategic system transition, enabling engineers to align interventions with the maturity and scope of each design challenge. It fuses core TRIZ instruments with the trends of engineering system evolution to couple contradiction handling with forward trajectories of system ideality. Applied to automotive BLDC applications, the method organizes recurrent issues such as acoustic anomalies, modal coupling, thermal stress, and control-layout interactions into an actionable roadmap that scales from quick design adjustments to modular, artificial intelligence-enabled capabilities. Experimental validation confirms the method’s practical impact: acoustic noise in the H24 configuration decreased by approximately 13%, modal vibration in the H8 case reduced by nearly 28%, and rotational imbalance amplitude in the rotor-yoke assembly dropped by around 55% after structural and dynamic optimization. The resulting framework is both prescriptive and extensible, guiding short-term fixes without foreclosing mid-term harmonization or long-term transformation, and generalizes to electromechanical product families that must balance cost, noise, durability, and intelligence under evolving requirements.

Keywords

Brushless Direct Current Motors / Cyclical Theory of Inventive Problem Solving / Roadmapping / Trends of Engineering System Evolution

Funding

None.

References

[1] Altshuller, G.S. (1984). Creativity as an Exact Science: The Theory of the Solution of Inventive Problems. Gordon and Breach Science Publishers, New York.

[2] Altshuller, G.S. (1996). The Innovation Algorithm: TRIZ, Systematic Innovation and Technical Creativity. Technical Innovation Center, India.

[3] Altun, K. (2025). A Maya calendar-inspired cyclical TRIZ approach: Enhancing systematic innovation and long-term problem-solving. International Journal of Systematic Innovation, 9(3), 8-19. https://doi.org/10.6977/IJoSI.202506_9(3).0002

[4] Altun, K., & Babayev, U. (2023). A novel approach to augment technology roadmapping through systematic innovation intelligence: A case of UAV technologies. International Journal of Systematic Innovation, 7(6), 1-11. https://doi.org/10.6977/IJoSI.202306_7(6).0001

[5] Boulkroune, A., Zouari, F., & Boubellouta, A. (2025). Adaptive fuzzy control for practical fixed-time synchronization of fractional-order chaotic systems. Journal of Vibration and Control. https://doi.org/10.1177/10775463251320258

[6] Cakmak, T., Altun, K., & Aksoy, M.O. (2021). Systematic customer value analysis: A case study in the automotive industry. International Journal of Systematic Innovation, 6(6), 22-36. https://doi.org/10.6977/IJoSI.202112_6(6).0004

[7] Ganesan, A., Jaiswal, R., & Pitchaikani, A. (2018). A study of an integrated HVAC-vehicle model for automotive vehicles. SAE International Journal of Passenger Cars Mechanical Systems, 11, 151-166. https://doi.org/10.4271/06-11-02-0013

[8] Ghane, M., Ang, M.C., Cavallucci, D., Kadir, R.A., Ng, K.W., & Sorooshian, S. (2022). TRIZ trend of engineering system evolution: A review on application, benefits, challenges and enhancement with computer-aided aspects. Computers and Industrial Engineering, 174, 108833. https://doi.org/10.1016/j.cie.2022.108833

[9] Lee, D.H. (2024). An improved sensorless control of BLDC motor using 1-shunt current sensor for HVAC of EV. In: 2024 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia). IEEE, United States, p1-6.

[10] Lee, D.W. (2014). Development of BLDC motor and multi-blade fan for HEV battery cooling system. International Journal of Automotive Technology, 15(7), 1101-1106. https://doi.org/10.1007/s12239-014-0114-7

[11] Mohanraj, D., Aruldavid, R., Verma, R., Sathiyasekar, K., Barnawi, A.B., Chokkalingam, B., et al. (2022). A review of BLDC motor: state of art, advanced control techniques, and applications. IEEE Access, 10, 54833-54869. https://doi.org/10.1109/ACCESS.2022.3175011

[12] Ravineala, T., Kurniawan, D., & Bennouna, S. (2025). Automotive HVAC blower blade pass noise sensitivity-a case study. INTER-NOISE and NOISE-CON Congress and Conference Proceedings, 271(2), 950-960. https://doi.org/10.3397/NC_2025_0163

[13] Rigatos, G., Abbaszadeh, M., Sari, B., Siano, P., Cuccurullo, G., & Zouari, F. (2023). Nonlinear optimal control for a gas compressor driven by an induction motor. Results in Control and Optimization, 11, 100226. https://doi.org/10.1016/j.rico.2023.100226

[14] Shao, J. (2006). An improved microcontroller-based sensorless brushless DC (BLDC) motor drive for automotive applications. IEEE Transactions on Industry Applications, 42(5), 1216-1221. https://doi.org/10.1109/TIA.2006.880888

[15] Sheu, D.D., Chiu, M.C., & Cayard, D. (2020). The 7 pillars of TRIZ philosophies. Computers and Industrial Engineering, 146, 106572. https://doi.org/10.1016/j.cie.2020.106572

[16] Sheu, D.D., & Chiu, S.C. (2017). Prioritized relevant trend identification for problem solving based on quantitative measures. Computers and Industrial Engineering, 107, 327-344. https://doi.org/10.1016/j.cie.2016.03.028

[17] Sheu, D.D., & Lee, H.K. (2011). A proposed process for systematic innovation. International Journal of Production Research, 49, 847-868. https://doi.org/10.1080/00207540903280549

[18] Singh, I. (2024). BLDC (Brushless Direct Current) Motors. Published in India 2024 by Pencil.

[19] Zouari, F., Saad, K.B., & Benrejeb, M. (2013). Adaptive Backstepping Control for a Class of Uncertain Single Input Single Output Nonlinear Systems. In 10th International Multi-Conferences on Systems, Signals and Devices 2013 (SSD13). IEEE, p1-6.